2015 Equity Derivatives Outlook

Transcription

Global Quantitative and
Derivatives Strategy
15 December 2014
2015 Equity Derivatives Outlook
Volatility Forecasts and Trade Ideas
Global Quantitative and
Derivatives Strategy
Marko Kolanovic
AC
(1-212) 272-1438
marko.kolanovic@jpmorgan.com
J.P. Morgan Securities LLC
Davide Silvestrini
AC
(44-20) 7134-4082
davide.silvestrini@jpmorgan.com
J.P. Morgan Securities plc
Tony SK Lee
AC
(852) 2800-8857
tony.sk.lee@jpmorgan.com
J.P. Morgan Securities (Asia Pacific) Limited/
J.P. Morgan Broking (Hong Kong) Limited
Bram Kaplan, CFA
AC
(1-212) 272-1215
bram.kaplan@jpmorgan.com
J.P. Morgan Securities LLC
Equity Derivatives & Delta-One
Strategy Team
US
Marko Kolanovic
mkolanovic@jpmorgan.com
Bram Kaplan
bram.kaplan@jpmorgan.com
AJ Mehra
arjun.mehra@jpmorgan.com
Min Moon
min.k.moon@jpmorgan.com
EMEA
Davide Silvestrini
Peng Cheng
Anders Armelius
Sahil Manocha
davide.silvestrini@jpmorgan.com
peng.cheng@jpmorgan.com
anders.armelius@jpmorgan.com
sahil.manocha@jpmorgan.com
Rahil Iqbal
rahil.iqbal@jpmorgan.com
Asia Pacific
Tony Lee
tony.sk.lee@jpmorgan.com
Sue Lee
sue.sj.lee@jpmorgan.com
Haoshun Liu
haoshun.liu@jpmorgan.com
Michiro Naito
michiro.naito@jpmorgan.com
Zhen Wei
zhen.wei@jpmorgan.com
See page 74 for analyst certification and important disclosures, including non-US analyst disclosures.
J.P. Morgan does and seeks to do business with companies covered in its research reports. As a result, investors should be aware that the
firm may have a conflict of interest that could affect the objectivity of this report. Investors should consider this report as only a single factor in
making their investment decision.
www.jpmorganmarkets.com
Marko Kolanovic
(1-212) 272-1438
Global Quantitative and Derivatives Strategy
15 December 2014
Contents
Equity Derivatives Outlook......................................................3
Outlook for Equity Risk ..........................................................................................3
Term Structure ......................................................................................................10
Skew.....................................................................................................................17
Implied Correlation ...............................................................................................23
Implied Dividends.................................................................................................27
Delta 1 Funding ....................................................................................................35
Derivatives Trades for 2015...................................................38
Macro/Directional Trades.......................................................38
Eurozone upside trades..........................................................................................38
Japan: Thematic trade ideas for the 3rd year of Abenomics ....................................40
China: Index and sector options to trade policy catalysts and market euphoria........42
China / Hong Kong relative value via outperformance options ...............................44
Cross asset strategy on Korean equity vs. currency correlation breakdown .............45
Long India low oil beneficiaries with smart hedging ..............................................46
Relative value between the European and US energy sectors..................................48
Trading US Financials outperformance via call switches, basket ............................49
Get on board the US Airlines industry ...................................................................51
Contrarian US Energy trade ideas..........................................................................52
ECB Sovereign QE: get upside exposure to Euro zone Banks.................................53
Trade our top US 2015 thematic stock ideas via baskets.........................................54
Europe thematic investment via TRS, basket and single stock options ....................55
Asia thematic investments: reforms of shareholder return enhancement..................57
Volatility/Risk Premia Trades ................................................58
Asia vs. DM volatility spreads - long volatility and carry .......................................58
S&P 500 vanilla dispersion....................................................................................60
Euro STOXX 50 dividends: 16s call spread collars ................................................61
Buy short-dated S&P 500 dividend swaps..............................................................62
Monetise the high implied funding spreads for Euro STOXX 50 long-dated TRS ...63
Hedging Trades ......................................................................64
Hedge the Japanification of the Eurozone with Euro STOXX 50 long-dated puts....64
FTSE hedges: Jun-15 knock-in put spreads and FX conditionality..........................65
Selling put ratios - taking advantage of cheap volatility and skew...........................66
Hedging a Japan armageddon scenario with long-dated volatility ...........................68
S&P 500 hedging strategy menu............................................................................70
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Equity Derivatives Outlook
Outlook for Equity Risk
2014 vs. 2015 Volatility
In order to forecast volatility in 2015, one first needs to look at historical levels, as volatility tends to persist in a recent
range and mean revert to long term averages. Figure 1 shows levels of short term implied volatility for Equities, Rates,
Commodities and FX, as well as credit spreads during 2014. In the first half of the year volatilities declined, reaching ~15
year lows during the summer of 2014. The increase in volatility during October’s growth scare was particularly sharp and
pushed volatility well above historical averages. In fact, Equity Volatility in October experienced one of the fastest
increases (and fastest subsequent declines) on record, pointing to thin market liquidity (Table 1).
In our 2014 volatility forecast, we predicted that volatility would increase in H2 2014 due to the end of the Fed’s QE
program and a turn in the rate cycle. October’s shock is an example of the market volatility we are likely to see in 2015 as
the Fed increases rates (the first rate hike is expected in June), and the market adjusts to lower levels of liquidity. Our view
is that volatility across assets in 2015 will look more like Q4 than H1 of 2014. This would translate into ~15% higher levels
of volatility compared to 2014 averages.
Figure 1: 1M implied volatility across assets in 2014 (levels on
1/1/2014 normalized to 100)
160
15 Year
Lows
140
Commodity
120
Average
Equity
Credit
FX
Rates
100
80
60
Jan
Feb Mar Apr May Jun
Jul
Aug
Sep
Oct
Nov
Table 1: Asset volatility in 2014 - 15-year context
Volatility
2014 Low 15Y %tile Max 1M Incr. 15Y %tile
S&P 500
10.3
1%
14.1
99%
SX5E
12.7
2%
16.5
98%
NKY
14.0
2%
13.1
97%
Hang Seng
11.5
0%
8.6
96%
G7 FX
5.1
0%
2.0
97%
EM FX
5.8
0%
1.8
94%
US Rates 1Y
80.8
7%
9.8
93%
US Rates 1M
52.3
1%
38.5
98%
Gold
10.8
2%
6.8
96%
Oil
11.5
0%
12.5
94%
IG Credit
55.0
24%
20.1
92%
HY Credit
291.2
9%
89.9
90%
Source: J.P. Morgan Equity Derivatives Strategy.
The median level of the VIX in 2014 was 13.4 (20th percentile since 1989) and S&P 500 realized volatility was 11% (28th
percentile since 1989). Volatility itself was highly volatile (high ‘vol of vol’), with S&P 500 1M realized volatility reaching
20 year lows in September (5.6%), only to exhibit the sharpest absolute increase since 2011 (13 points or 127%) in
October. Low liquidity and market positioning contributed to this unusual pattern. Record levels of call to put imbalance
caused dealers to be long gamma in August and early September. Long gamma exposure and low levels of market activity
caused the S&P 500 to get pinned at 2,000 for several weeks (Figure 3), pushing realized volatility to 20 year lows. The
fast pace of the market selloff and volatility increase in October, with little change in fundamentals, points to high levels of
liquidity risk. Equally impressive was the subsequent market rally and decline in volatility helped by investors selling
volatility via listed options, inverse VIX ETNs, and ‘smart beta’ over the counter products.
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Figure 2: S&P 500 1M realized volatility and the VIX
20%
1M Realized
Figure 3: S&P 500 pattern around October selloff
VIX
18%
25
15%
October
Spike
Scramble for Yield
20
13%
10%
S&P Pinned at 2000
15
8%
5%
Selloff in Poor Liquidity
10
Jan
Mar
May
Jul
Sep
Nov
Volatility Fundamentals
The turn in the interest rate and liquidity cycle will put upward pressure on volatility and would support mean reversion
toward higher long-term average levels. These technical factors need to be compared to macro fundamentals that are another
important driver of volatility. In our previous Outlook publications, we have demonstrated a relationship between GDP,
unemployment, equity earnings and corporate default rates to levels of equity volatility. J.P. Morgan forecasts for these
variables suggest that volatility is likely to be contained during 2015. In particular, US GDP is expected to rise and
unemployment to fall, while our equity strategists forecast continued growth in corporate earnings and stable equity
multiples (Figure 4). The trend in improving macro fundamentals will counter upward pressure on volatility coming from
the rate cycle.
Figure 4: JPM Economics/Strategy forecasts
Figure 5: Annual US equity returns vs. GDP
Latest
Observation 2015 Forecast Change
Macroeconomic Data
Global GDP (FY)
US GDP (FY)
Euro Area GDP (FY)
US Unemployment
Equity
US
Europe
Asia ex-Japan
Japan
Credit
IG Credit (bps)
HY Credit (bps)
Rates
Fed Funds Rate
DM CB Rates
EM CB Rates
3M USD LIBOR
US 3Y Treasury Yield
US 10Y Treasury Yield
3.00%
2.30%
0.90%
5.80%
3.40%
3.00%
1.60%
5.40%
0.40%
0.70%
0.70%
-0.40%
2002
1342
461
1400
2250
1550
525
1700
12.4%
15.5%
14.0%
21.5%
72
392
60
320
-12
-72
0.13%
0.26%
6.15%
0.24%
0.97%
2.08%
1.00%
0.68%
6.09%
1.05%
2.00%
2.80%
0.88%
0.42%
-0.06%
0.81%
1.03%
0.72%
S&P 500
45%
30%
2012 2010
2014
15%
2011
0%
-4
-2
2013
2009
0
2
4
6
8
10
-15%
-30%
US GDP YoY
-45%
More difficult to estimate is the extent to which low current levels of volatility are already anticipating an improvement in
macro data. Figure 5 shows YoY changes in real GDP over the past 65 years and equity market returns. One can notice that
in 5 out of last 6 years, equity market returns were above the historical trendline, raising the possibility that strong
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fundamentals may already be priced into low levels of volatility. A historical regression analysis of the VIX vs. levels of
nearly 100 macro time series covering labor, consumer, housing, manufacturing and sentiment data, also supports this
conclusion. The analysis suggests that the VIX may be 0.8 standard deviations or ~5 points too low relative to current macro
data.
To further investigate possibility of current low levels of volatility being already suppressed below fundamental levels, next
we analyze various measures of volatility premia, leverage and flows.
Volatility Premia and Positioning
Equity volatility premia have been steadily declining over the past 3 years.1 In our view, this is in part driven by central
bank policies that reset the level of available yields lower, and pushed investors into higher risk strategies both by depriving
them of yield and potentially lulling them into complacency by providing an implicit market backstop. Figure 6 shows the
compression of VIX options (1M straddle) and term structure (2M-1M rolldown) risk premia.2 Figure 7 shows S&P 500
options term structure premia (6M-3M rolldown) and average implied-realized volatility premia for S&P 500 stocks. All of
these risk premia contracted and are currently close to zero. This suggests excessive supply of volatility risk premia through
yield generating strategies, combined with lower demand for equity protection.
Figure 6: VIX risk premia
Figure 7: Stock and index risk premia
5
10%
VIX Option Premia (1M)
3
S&P 500 Term Premia (6M)
8%
6%
4%
1
2%
0%
-1
-2%
-3
Oct, 11
Jun, 12
Feb, 13
Oct, 13
Jun, 14
-4%
Oct, 11
Jun, 12
Feb, 13
Oct, 13
Jun, 14
12%
VIX Term Premia (1M-2M)
4
Stock Volatility Premia (3M)
10%
8%
6%
2
4%
2%
0
0%
-2%
-2
Oct, 11
Jun, 12
Feb, 13
Oct, 13
1
2
Jun, 14
-4%
Oct, 11
Jun, 12
Feb, 13
Oct, 13
Jun, 14
Equity Volatility risk premia is the compensation an investor receives for being short equity risk via a derivative product.
For more details see our report VIX Risk Premia and Volatility Trading Signals.
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Short Volatility Carry Strategies
As discussed above, volatility risk premia generally compressed in 2014, leading most equity volatility selling strategies to
deliver worse information ratios and larger draw downs compared to prior years. The highest risk-adjusted returns out of a
selection of delta hedged straddles, outright straddles, short variance swap and short V2X/VIX futures, were observed for
short 1M variance swaps on the S&P500 and 1M delta-hedged straddles on the Nikkei and the FTSE.
Table 2: Information ratios and 2014 max draw downs for a selection of equity derivatives carry strategies
2011
2012
2013
2014 YTD*
S&P500
0.88
1.54
-0.03
-0.14
Max draw
down in 2014
-2.3%
FTSE
1.42
1.44
-0.62
0.70
-1.2%
DAX
0.01
0.52
-0.46
-1.03
-3.7%
Nikkei
2.95
2.17
-1.19
0.77
-2.4%
Euro STOXX 50
0.21
0.62
-0.84
-0.85
-3.7%
Average
1.09
1.26
-0.63
-0.11
-2.7%
S&P500
0.23
-0.41
-1.04
-0.01
-10.2%
FTSE
0.46
-0.01
-1.46
-0.77
-10.8%
DAX
-0.27
-1.33
-1.79
-1.20
-20.2%
Nikkei
0.29
-0.62
-1.34
-0.73
-25.4%
Euro STOXX 50
0.11
-0.69
-1.09
-0.65
-17.1%
Average
0.32
-0.30
-1.22
-0.67
-16.7%
S&P500
-0.20
4.16
1.84
1.33
-6.2%
Euro STOXX 50
0.21
2.09
0.72
0.05
-7.8%
-11.3%
Strategy information ratios
Delta hedged 1M ATM
straddles
Outright 1M ATM
straddles
Short 30d Var swaps*
Short VIX/V2X futures**
Nikkei
-0.25
1.95
-0.59
-0.05
Average
-0.08
2.73
0.66
0.44
-8.4%
VIX
-0.58
2.25
1.81
0.18
-45.5%
V2X
-0.67
2.61
1.47
-0.19
-39.4%
Source: J.P. Morgan Equity Derivatives Strategy. *1M variance swap initiated daily with vega notional of 2.5bps of previous day’s level. ** Inverse return of Short-term VIX/V2X futures index. * as
of 9-Dec-14
These strategies may become more attractive when volatility premia widen, as we think they will begin to do next year.
Several other datasets point to increased levels of leverage and financial risk taking. For instance hedge fund equity
exposure (beta of HFRX to S&P 500) recently rose to near record levels and inflows into equity mutual funds and ETFs
accelerated (Figure 8).3 Figure 9 shows the percentage of US household assets allocated to equities (expressed as % of
global equity capitalization) and NYSE margin debt (expressed as % of S&P 500 capitalization). While none of these
measures can predict a market correction and spike in volatility, they clearly demonstrate increased levels of risk taking and
perhaps risk complacency.
As the rates and liquidity cycle turn in 2015, we believe levels of risk premia are likely to widen from current record lows.
3
It is often argued how the current level of HF leverage is much lower now as compared to pre-crisis year and hence the
level of risk in the system is lower. According to data from our prime services, HF leverage is indeed lower now, but much
of the leverage reduction came from market neutral quantitative strategies (whose unwind was not likely to affect the overall
market in the first place).
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Figure 8: Hedge Fund leverage and Mutual Fund / ETF flows
0.40
Figure 9: NYSE margin debt and US household equity holdings
800
HF Beta to the S&P 500
0.35
700
MF and ETF Equity Inflows ($Bn)
0.30
600
0.25
500
0.20
400
0.15
300
0.10
200
0.05
100
39%
1.0
NYSE Margin Debt (% S&P 500 Mkt Cap)
US HH Equity Allocation (% of Global Mkt Cap)
37%
0.5
35%
33%
0.0
31%
-0.5
29%
-1.0
0.00
2007
0
2008
2009
2010
2011
2012
2013
2014
-1.5
2004
27%
25%
2006
2008
2010
2012
2014
Correlation Risk
In addition to asset volatility, levels of correlations are another important driver of a portfolio risk. For long-short managers,
high correlation also impacts portfolio returns by limiting managers’ ability to generate alpha. While correlations have
declined from 2011 peak levels, average levels are substantially higher that what was observed in other periods of low
volatility over the past 20 years. Figure 10 shows the average level of correlation of S&P 500 stocks and sectors. One can
notice that sector correlations are particularly high, indicating the importance of macro factors that drive correlation.4 In
addition to macro factors, in our previous research (Why We Have a Correlation Bubble) we have argued that structural
developments caused a structural increase in market correlations.
Figure 10: S&P 500 sector and stock correlation over the past 20
years
Figure 11: Correlation levels during October’s spike were similar to
those in the 1997/8 Asia Crisis and 2002 market bottom
90%
S&P 500 Sector
Correlation
60%
80%
Asia Crisis
Russia Default
80%
50%
70%
2002
Market Bottom
Oct '14
60%
60%
40%
40%
50%
30%
40%
20%
10%
1994
S&P 500 Stock
Correlation
30%
20%
1997
1999
2002
2004
2007
2009
2011
20%
2014
0%
1994
1997
1999
2002
2004
2007
2009
2011
2014
We believe that recent changes in correlation levels also point to low market liquidity, and elevated risk of a correlation
spike similar to the ones we saw in 2010 and 2011. Figure 12 shows a 20 year history of S&P 500 stock correlation levels.
We note that this October, 1M correlation reached ~60% - similar to levels seen during the 1997/98 Asia Crisis/Russia
Default and 2002 market bottom. Given that there was no major financial or economic crisis this October that would
warrant such a sharp increase, we believe this reflects the market's vulnerability to liquidity driven correlation shocks.
4
For instance, Central bank meetings and rate policy decisions, Commodity prices, geopolitical developments, etc.
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Despite the perception that low levels of volatility and declining correlations are the environment most suitable for stock
picking, we believe this is far from the truth. Figure 12 shows average level of stock volatility and correlation for S&P 500
stocks over the past 20 years. One can notice the gap between the elevated levels of correlation (~65th historical percentile)
and low levels of volatility (~15th historical percentile) is near record levels, resulting in a very unfavorable environment for
stock pickers. For instance, the average stock tracking error – a measure of alpha available to a long short manager – is
currently at all time lows. It should not come as a surprise therefore that 2014 is on track to be one of the worst years for
hedge fund closures since 2009 (461 HFs closed in the first half of 2014, compared to 1023 closed in 2009).
Levels of dispersion are not equal across the market, and some sectors provide better opportunities to stock pickers than
others. Figure 13 shows the average levels of stock volatility and stock correlation in each of 10 S&P 500 sectors. One can
notice that Energy and Discretionary sectors have relatively favorable levels of dispersion. Technology and Materials have
below average correlations, and Health Care has the highest average stock volatility (albeit only in the 24th historical
percentile).
Figure 12: Average S&P 500 stock volatility and correlation
67%
Average Stock
Correlation
S&P 500 Sector
57%
47%
37%
27%
17%
1994
Average Stock Volatility
1997
1999
2002
2004
Figure 13: Average stock volatility and correlation for each of 10 S&P
500 sectors
2007
2009
2011
2014
C. Discretionary
C. Staples
Energy
Financials
Health Care
Industrials
Technology
Materials
Telecomms
Utilities
Average
Stock Volatility
%-tile
Level
11
22.9%
3
16.5%
17
21.4%
0
17.4%
24
22.6%
2
18.2%
1
23.4%
2
21.0%
0
17.6%
17
16.4%
2
20.4%
Correlation
%-tile
Level
47
31.5%
53
32.1%
39
48.9%
68
52.0%
77
37.1%
79
52.1%
16
30.5%
35
38.7%
60
50.0%
76
62.7%
62
43.6%
Summary of Forecasts
In summary, we expect volatility levels to increase with an average VIX level of 16 (median of 15) in 2015. As the rates
and liquidity cycle turn, we think there is a higher chance of volatility spikes like the one we observed in October, and think
that levels of risk premia are likely to widen from current record lows.
Below we highlight some region-specific drivers of volatility in Europe and Asia.
Europe: We expect 2015 to be more event-rich than 2014, especially in H1. Following a slightly disappointing TLTRO
announcement, our economists have revised their view on the ECB and now expect that Sovereign QE and purchases of
corporate bonds will be announced in the January 22nd meeting, after the ECJ will publish their opinion on the legality of
the ECB’s OMT program on the 14-Jan. On top of the great expectations on the ECB, next year we will have elections in
the UK, Spain and potentially Greece and Italy, which will all likely see the rise of non-mainstream, largely Euro-skeptic
political parties. Furthermore, the tension between Ukraine and Russia will likely persist and the situation in Eastern
Ukraine will remain fluid.
We expect European volatility to be sustained relative to the US in H1, as Draghi continues to fight the hawkish members of
the ECB board. Although our economists’ base case is for an announcement of QE in the next ECB meeting, this outcome is
far from guaranteed. Additionally, the path to the ECB expected balance sheet expansion is unlikely to be straightforward,
and the dissonant public declarations from the doves and hawks on the ECB board will remain a feature of European
markets in H1-2015, in our view.
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We will likely see more volatility to the upside in H1-15 should Sovereign QE be announced, as this announcement would
lead to a temporary tapering of the overwriting flows which helped keep European vols low and cheap in 2014. We might
also see Japan-like flow dynamics in the short-end of the volatility curves, as international investors and macro players
position for European upside via calls, although we think that the impact of these flows would be more muted than in Japan.
Should the ECB fail to deliver any substantial measures, investors will likely become increasingly concerned about
deflationary pressures, a scenario which would likely see volatilities well supported and long gamma delivering.
Our base case is that the relative outperformance of European volatilities vs. the US will subside in H2 as the European
economy picks up pace, the ECB provides support to the market and inflows into European equities come back. Overall we
expect the VSTOXX less VIX spread to trade close to its historical average over the year (Figure 14).
Figure 14: We expect the spread between VSTOXX and VIX to be
above historical average in 1H-15 and decline in 2H-15, and overall
average around 4 volatility points, similar to 2014
VSTOXX less VIX average intraday spread
2011 avg: 5.9
12%
2012 avg: 6.7
10%
2013 avg: 4.2
10
8
2014 avg: 4.0
6
4
2
Long-term average: 4.1
0
14%
Avg Absolute Quarterly Move
12
Figure 15: Average absolute quarterly move versus quarterly
realized volatility over past 10 years
Avg EM Asia (HSI, HSCEI, KOSPI2, TWSE, NIFTY)
Avg DM Asia (NKY, AS51)
Avg US & Europe (SPX, SX5E)
8%
6%
4%
2%
Source: J.P. Morgan Equity Derivatives Strategy. As of 12-Dec-14
Jul-14
Jan-14
Jul-13
Jan-13
Jul-12
Jan-12
Jul-11
Jan-11
-2
0%
Below 10%
Between 10% - Between 15% - Between 20% - Between 25% 15%
20%
25%
35%
Quarterly Realized Volatility
Source: J.P. Morgan Equity Derivatives Strategy, Bloomberg.
Asia: In terms of local risk factors, while further monetary easing and progress in financial reform will continue to support
the stock market performance in China, market participants may have underestimated another important factor, which is that
the Chinese government will try their best to prevent systemic financial risk. Tightening rules on shadow banking and local
government debt, and now on bond market, is a key theme in this context. This is important especially as implicit
guarantees cause market distortions. Overall, the combination of policy support to stabilize near term growth and ongoing
reforms designed to reduce systemic risks will continue to heighten volatility in China's financial markets. For Japan, the
risk of policy failure, i.e. economic impact of structural reforms falling short of expectations, will be the main volatility
driver. However, the renewed presence of domestic investors may contribute to lower volatility. With the Government
Pension Investment Fund (the largest government pension fund in the world) increasing weight of domestic equities, other
institutional investors are likely to follow in its footsteps. Once equity allocation is set, the behavior of institutional investors
is to sell equities when the share prices rise and buy them back when the prices fall, thus contributing to the lowering of
market volatility as a whole.
Given uncertainty on central bank policies is a major risk to manage in 2015, we suggest bracing for a higher volatility
environment with options, as Asian options offer attractive risk-reward for both directional and volatility investors.
Historically, the high beta and trending nature of Asian markets has resulted in significant price swings in terms of absolute
price moves across various volatility scenarios (Figure 15). During a moderately higher volatility environment than the one
we are experiencing today (i.e. between 15% and 25% realized volatility), the average quarterly moves exhibited by Asia
indices have been greater than the average quarterly moves in the US and European indices. This analysis reinforces the
notion that Asia can have relatively larger directional moves than DM indices under a similar volatility environment, which
should improve the profitability and breakeven attractiveness of owning options in this region. Hence we suggest bracing
for a higher volatility environment in 2015 with options.
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Term Structure
Term structures across most major global indices outside of Japan were upward sloping throughout most of 2014, as muted
realized volatility continued to pin down short-dated implied vol levels (Figure 16). The Nikkei again had a flat/inverted
term structure this year as Abenomics 2.0 and market reaction to a shift in GPIF’s benchmark toward equities drove realized
volatility higher. European indices exhibited flatter term structures on elevated realized volatility as investors fretted about
further ECB stimulus. Table 3 shows the current 12M-3M term structure across global indices, and compares their YTD
averages to last year. We note that most major Western index term structures flattened this year, as long-dated volatilities
came down and realized volatility stabilized after recording declines in the prior 2 years. Below we discuss the volatility
term structure drivers for each region in greater detail.
Figure 16: SPX term structure remained the steepest among major
global indices this year...
12M-3M ATM implied volatility spread
4%
2%
0%
-2%
SPX
SX5E
NKY
HSI
-4%
-6%
-8%
Jan-13
Jul-13
Jan-14
Jul-14
Table 3: …while all global index term structures are upward sloping,
apart from NKY
12M-3M ATM
Vol Spread
Current
3Y %ile
YTD
Average
2013
Average
SPX
3.1%
72%
2.6%
2.6%
NDX
3.1%
65%
2.3%
2.9%
RTY
2.1%
36%
2.0%
2.3%
SX5E
1.2%
32%
1.4%
2.0%
UKX
2.4%
63%
1.9%
1.9%
DAX
1.6%
38%
1.4%
2.2%
NKY
-1.1%
30%
0.1%
-2.0%
HSI
0.9%
17%
1.9%
1.5%
AS51
1.5%
18%
2.2%
1.7%
KOSPI2
1.9%
53%
2.4%
1.5%
Source: J.P. Morgan Equity Derivatives Strategy. Data as of 5-Dec-2014
US: US major index vol term structures remained upward sloping nearly the entire 2014, except for brief periods of frontend inversion in February and October when the S&P 500 pulled back ~6% and ~7%, respectively. Realized volatility was
muted again this year, keeping downward pressure on the short-end of the term structure. S&P 500 realized volatility is
close to unchanged YTD vs. 2013 at ~11%, while NASDAQ and Russell 2000 realized vols rose ~1.5% YoY, but remain
near cycle lows. Unlike Asia and Europe, where structured product issuance is the main driver of long-dated volatility,
volatility was historically driven by the demand for long-term protection from the insurance industry to hedge their variable
annuity products. As in past years, the combination of these short- and long-end term structure effects led the S&P 500 to
have the steepest average term structure among major global indices in 2014 (Table 3). In 2014, the term structure
continued to flatten on average as short-dated S&P 500 implied volatilities were little changed but long-dated volatilities
continued to fall in H1 (Figure 17).
Since the year started out quiet on the long-dated hedging front and the market continued to grind higher, 5-10Y volatility
levels receded in H1 this year to their lowest since the 2008 financial crisis. Flows on long-dated volatility indicate
significant hedging demand in two waves in the summer and October (likely driven by insurers opportunistically adding
vega hedges as long-term vol levels fell to 7-year lows) which arrested and then fully reversed the declines in long term
volatility from the first half of the year (Figure 18). The surprise decline in US rates this year may have also contributed to
additional hedging demand, since VA liabilities increase as rates fall. Anecdotally, insurance hedging demand was stronger
overall this year than in 2013, but remains considerably lighter than in the prior few years. As we highlighted in our 2014
Outlook, insurance hedging flows have waned in recent years as a number of Variable Annuity issuers scaled back or
shuttered their businesses after sustaining losses in the Global Financial Crisis, while new VA products being issued have
shifted towards using volatility/risk control indices, charging higher fees and offering less generous features, and thus have
lower demand for hedges5.
5
See Variable Annuity Market Trends, Jimmy Bhullar, 24-Nov-2014 for additional details on the VA market
10
15 December 2014
Marko Kolanovic
(1-212) 272-1438
We note US structured product flows continue to have a relatively low impact on long-dated S&P 500 volatility. According
to StructuredRetailProducts.com, total issuance in the US for S&P 500-linked structured products was ~$7Bn in annualized
notional (as of late-November), down from an average of ~$10Bn in the previous 4 years. Moreover, ~45% of all structured
products issued in the US this year (across all asset classes) had a tenor of less than 2 years. As a back of the envelope
calculation (to put this issuance number into context), if we assume that the remaining ~55% of S&P 500 linked issuance
has an average 5-year life to expiry and all embed long ATM call options6 on the S&P 500, this would result in net buying
of less than $30Mn vega over the entire year. By comparison, the S&P 500 listed options market has ~$2.5Bn vega notional
in open interest.
Figure 17: The long-end of the SPX variance curve shifted lower on
average this year as hedging demand remained weak during the H1,
but rebounded following waves of VA hedger activity in Aug/Oct
S&P 500 Variance Strike
Figure 18: Hedging demand in summer/early fall reversed the YTD
decline in long-dated S&P 500 volatility, even as the marked rallied
35%
5Y Variance
32%
30%
28%
24%
25%
20%
2014 YTD Avg
2013 Avg
2012 Avg
maturity (months)
5-Dec-14
16%
12%
0
12
24
36
48
60
72
84
96
108 120
20%
Jan-12
Jul-12
Jan-13
Jul-13
Jan-14
Jul-14
Significant monetization of short-dated volatility carry pressured the front end of the term structure this year. The VIX term
structure flattened again this year as the supply-demand picture continued to tilt towards VIX sellers. The VIX term
structure was upward sloping most of the year, with a brief front-end inversion during the spike in February (when the VIX
peaked at 21) and nearly full inversion in October (when the VIX spiked to 26).
In 2010/11, the front end of the VIX term structure was steepened by large investment into systematic long volatility ETNs
like the VXX and TVIX (since the products rebalance by buying the second month futures and selling the front month every
day). However, over the last couple of years, significant investment in products designed to extract the VIX term structure
premium has created a more balanced supply-demand picture. In our view, this shift in positioning is a key driver of the
flattening of the VIX term structure in the last couple of years, which has appreciably reduced the cost of carrying long VIX
futures positions (Figure 19). Figure 20 shows the exposure-weighted7 net assets in short-term VIX ETNs, by taking the
difference between the funds’ shares outstanding and short interest. This measure was negative or close to flat throughout
2014, and turned sharply negative during the brief market sell-offs in February and October. The large investment in short
VIX ETNs XIV and SVXY during these brief episodes of market weakness, suggest many investors are complacent to the
risk of large or prolonged spikes in volatility.
6
This assumption will significantly overstate the net vega exposure of S&P 500-linked structured products. Many products will be long
call spreads/capped calls which have lower vega exposure than calls, or short OTM puts (e.g. via reverse convertibles) which have a
negative vega exposure, etc. and thus the net vega exposure of all structured product issuance this year is likely much lower.
7
For example, a 2x levered ETN’s AUM is doubled, a 1x inverse VIX ETN’s AUM is multiplied by -1 in the calculation
11
15 December 2014
Marko Kolanovic
(1-212) 272-1438
Figure 19: VIX futures’ carry cost continued to decline in 2014
Figure 20: The effective VIX ETN exposure was negative most of
2014, and reached a record short in the Oct market sell-off
VXX Level (Logarithmic scale)
USD Mn
VXX
Slope (2012)
Slope (2013)
Slope (2014)
4000
~33bps/day
carry cost
200
Exposure-weighted AUM
in VIX Short-Term ETPs
net of Short Interest
3000
2000
~23bps/day
carry cost
~60bps/day
carry cost
1000
0
-1000
20
Jan-12
Jul-12
Jan-13
Jul-13
Jan-14
-2000
2009
Jul-14
2010
2011
2012
2013
2014
We expect VA hedging demand for long-term volatility to remain relatively subdued next year, and thus do not anticipate a
significant steepening of the S&P 500 term structure. JPM Insurance analyst Jimmy Bhullar expects VA sales to rise 7.9%
next year, but new products continue to be de-risked, and thus are unlikely to drive an acceleration in hedging demand until
VA issuers begin issuing more aggressive products (e.g. if sparked by competitive pressures). Most of the incremental
demand for VA hedging comes from new issuance, as insurers (who wish to do so) likely already have hedges in place on
their legacy books. That said, our analyst notes the risk in legacy VA blocks has declined thanks in part to the strong equity
market, but living benefit guarantees still pose considerable risk in a tail scenario. Thus a strong market pullback could
potentially drive some incremental long-dated hedging demand by insurers to stem further losses.
Europe: Up to the October sell off, European index volatility term structures traded steep relative to history for most of the
year, inverting only briefly in Q1. Across major European indices (Figure 21), the FTSE had the steepest volatility term
structure over the year, despite the strong but short-lived impact that political uncertainty around the September Scottish
referendum had on the curve. The SX7E index had the flattest term structure over the year, with the 1Y-3M ATM vol
spread averaging only 0.5% prior to the October correction. In the periphery, the IBEX term structure was slightly steeper
than last year while the FTSEMIB was flatter and notably both indices inverted to a similar degree in October. The DAX
and the Euro STOXX 50 term structures mirrored each other closely for most of the year but the latter inverted to a much
greater degree in October.
Figure 21: European term structures were mostly steep relative to
history in 2014 but reacted strongly in the October correction
Figure 22: Longer-dated vol declined on average over the year
across major European indices
1Y – 3M ATM Implied Vol Spread (both axis)
Volatility points
0%
-3%
0.0%
-5%
Source: J.P. Morgan Equity Derivatives Strategy
12
SX7E
-4%
SMI
-4%
UKX
0.5%
DAX
-2%
SX5E
-3%
SX7E
1.0%
FTSEMIB
-1%
IBEX
-2%
SMI
1.5%
DAX
0%
SX5E
-1%
UKX
2.0%
FTSEMIB
Decline in avg. 3Y ATM vol 2014YTD vs. 2013
CAC
Oct inversion (RHS)
IBEX
Avg. 2014 1Y-3M ATM vol spread prior to Oct correction
2.5%
15 December 2014
Marko Kolanovic
(1-212) 272-1438
Average long-dated implied volatilities declined across all major European indices compared to last year, reaching multiyear lows mid-year, with the SX7E and IBEX long-dated vols experiencing the largest falls (Figure 22). The decline in
IBEX long-dated implied volatility is particularly notable when compared to that of the FTSEMIB. The two indices’3Y
volatilities tracked each other closely throughout 2013 and H1-14, but started to diverge around May, possibly reflecting
market expectations of better growth potential for Spain vs. Italy and a significantly higher structured product issuance on
the IBEX than the FTSEMIB during the year (Figure 24). Indeed, the IBEX was in the top 10 of European underliers for
structured product issuance most months in 2014, while the FTSEMIB featured in the top 10 list only once.
Figure 23: Longer-dated vols reached multi-year lows in 2014 and
are likely to continue on their upward trend in 2015, in our view
Figure 24: Spanish longer-dated vols declined more than Italian
ones in 2014
3Y ATM Implied Vol
3Y ATM Vol (Vol points)
Nov-14
Sep-14
Jul-14
May-14
Mar-14
Dec-09
Apr-10
Aug-10
Dec-10
Apr-11
Aug-11
Dec-11
Apr-12
Aug-12
Dec-12
Apr-13
Aug-13
Dec-13
Apr-14
Aug-14
Dec-14
14%
IBEX
Jan-14
19%
Nov-13
24%
FTSEMIB
Sep-13
29%
0.26
0.25
0.24
0.23
0.22
0.21
0.2
0.19
0.18
Jul-13
DAX
May-13
UKX
Mar-13
SX5E
Jan-13
34%
During the October correction, European term structures experienced the largest inversions amongst global indices, with the
Euro STOXX 50 1Y-3M vol spread reaching 2010/2011 levels. Unlike 2010/2011, however, the Euro STOXX 50 volatility
term structure quickly reverted to upward sloping (Figure 26). We expect this term structure behavior to continue into 2015,
with spikes in short-dated volatility quickly fading against the backdrop of rising longer-dated implied volatilities, which we
expect to increase from the multi-year lows reached in mid-2014 (Figure 23).
Figure 25: The VSTOXX term structure mirrored that of the VIX for
most of the year. The divergence seen since the October correction
is likely to be sustained heading into 2015, in our view
Both axis: Curve steepness for front 6 contracts (vol point per month)
1.5
1
0.5
0
-0.5
-1
Source: J.P. Morgan Equity Derivatives Strategy. As of 9-Dec-2014.
V2X
Sep-14
VIX
May-14
Jan-14
May-13
Jan-13
Sep-13
VIX less V2X (RHS)
-1.5
1.4
1.2
1
0.8
0.6
0.4
0.2
0
-0.2
-0.4
Figure 26: The Euro STOXX 50 term structure was inverted for a few
days in 2014, but the inversion was sharp
Minimum 1Y-3M ATM vol spread recorded over the year (volatility points)
0%
-1%
-2%
-3%
-4%
-5%
-6%
-7%
-8%
-9%
-10%
2013
2012
2010
2014
2011
0
20
40
60
80
100
120
140
Number of days where TS was inverted
During most of 2014, the steepness of the VSTOXX futures term structure mirrored that of the VIX. Since the October
correction, however, the VSTOXX term structure has been trading considerably flatter, reflecting heightened uncertainty on
13
Marko Kolanovic
(1-212) 272-1438
15 December 2014
ECB action into 2015 (Figure 25). This dynamic is likely to persist in the beginning of next year, while we expect it to
subside in H2 as we get more clarity European monetary policy, which in our view will likely lead to a reversion of the
VSTOXX futures term structures to the levels of steepness recorded last year and in the first half of 2014.
Asia: In 2014, term structures in Nikkei 225 and H-shares observed inversions while the rest of Asia maintained upward
sloping term structures, with volatility realizing post-GFC low levels. In Japan, the singular focus on the Bank of Japan’s
commitment to achieve the 2% inflation target amid volatility injected by the consumption tax hike led to the market
becoming highly sensitive to policy induced uncertainties. This is shown in the strong correlation between Japan Economic
Policy Uncertainty Index and Nikkei 225 term structure (Figure 27). For China, a brief period of term structure inversion
was seen between February and March 2014 in H-shares as increased concerns on the China hard landing and a sharp
downward revision in consensus GDP forecasts (more so in 2014 relative to 2015) led to a great deal of risk premium being
priced into the short term implied volatility (Figure 28). H-shares term structure later normalized and remained upward
sloping until November when People’s Bank of China surprised the market with the first rate cut since 2012. Amid the
market rally, short-dated volatility strongly outperformed longer-dated ones due to overwhelming upside exposure demand
via options.
Figure 27: Policy related economic uncertainty inverts volatility term
structure in Nikkei 225
Volatility spread
Figure 28: H-shares term structure reflects relative revisions between
2014 and 2015 China GDP forecasts
Index Volatility spread
10%
8%
3.0
-0.08
190
2.0
-0.06
170
6%
150
2%
110
-1.0
90
-2.0
-2%
-0.02
0.0
130
70
-0.04
1.0
4%
0%
%
210
0.00
0.02
0.04
-3.0
0.06
50
-4%
Jan-13 Apr-13
30
Jul-13
NKY 3M-12M IV Spread
Oct-13 Jan-14 Apr-14
Jul-14
Oct-14
Japan Economic Policy Uncertainty Index (R)
Source: J.P. Morgan Equity Derivatives Strategy, “Measuring Economic Policy Uncertainty” by
Scott Baker, Nicholas Bloom and Steven J. Davis at www.PolicyUncertainty.com
-4.0
Nov-13
0.08
Feb-14
May-14
Aug-14
Nov-14
HSCEI 3M-12M IV Spread
China GDP Consensus 4W Relative Change: 2014 - 2015 (Inverted, R)
Source: J.P. Morgan Equity Derivatives Strategy, Bloomberg
On the back end of the curve, the issuance of structured products continued to weigh on longer-dated volatility, particularly
in KOSPI 200 and H-shares, which are the most popular underlyings for the autocallables issued in Korea, but to a lesser
extent in Nikkei 225 as the issuance activities tapered off rapidly in Japan following the oversupply from last year (Figure
29). Despite the low levels of long-dated volatility on an absolute term, short volatility strategies in Asia ex-Japan, both
outright and via calendar spreads, remained profitable due to record low realized volatility and steep term structure (Table
3). These carry trades may continue to provide opportunities in selected Asian indices with low risk of short-term volatility
spikes, such as KOSPI 200.
14
Marko Kolanovic
(1-212) 272-1438
15 December 2014
Figure 29: Retail structured products issuance recorded a historical
high in Korea but slowed down in Japan.
Notional (JPY bn)
Notional (KRW tn)
Table 4: Short long-dated volatility outright or via calendar spreads
performed well in Asia ex Japan due to low realized volatility and
upward sloping term structure
HSCEI
29.1%
27.9%
30.3%
1.2%
65%
SX5E
23.1%
21.6%
24.5%
1.5%
87%
UKX
19.6%
18.1%
21.0%
1.5%
72%
SPX
20.8%
19.1%
22.4%
1.7%
81%
PnL of Short 1Y Varswap over past 1 year
Average
0.5%
5.4%
Min
-7.2%
2.3%
Max
7.2%
9.0%
5.5%
3.0%
7.8%
5.4%
3.1%
7.4%
6.0%
4.7%
8.3%
4.7%
2.2%
7.4%
6.1%
3.9%
7.7%
5.2%
2.7%
8.2%
PnL of Short 1Y-2Y Forward Variance Swap over past 1 year
Average
-0.2%
2.0%
2.6%
2.9%
Min
-5.9% -2.4% -1.4% -0.9%
Max
5.8%
6.3%
6.1%
4.6%
2.8%
-2.8%
5.9%
3.5%
0.2%
5.9%
3.1%
0.0%
5.2%
2.1%
-1.5%
5.5%
Curr 2Y Vswap (1)
Curr 1Y Vswap (2)
Curr 1Y-2Y Fwd Vswap (3)
Spread (1)-(2)
Spread 10Y Percentile
Source: J.P. Morgan.
*2014E figures are estimated by annualizing the issuance up to Oct
2014. Japan issuance data is based on the public issuance only and therefore may not represent
an accurate picture. Private placements can be 1~1.5 times larger in notional.
NKY
27.3%
27.4%
27.1%
-0.1%
22%
AS51 KOSPI2
HSI
19.9%
21.6% 24.0%
18.2%
19.6% 21.9%
21.4%
23.4% 26.0%
1.7%
2.0%
2.1%
66%
87%
82%
Source: J.P. Morgan. * Data as of December 5, 2014
Note: PnL calculated as (δ^2 - K^2)/2K where δ = realized volatility and K = variance swap strike.
5% bid/ask spread (as percentage of vol points) were used to enter/unwind the trade.
One noteworthy development in Asia is a meaningful pick up in the VNKY futures open interest/volume. After the launch
of VHSI and VNKY futures in February 2012, VNKY managed to start gaining liquidity this year ( Figure 30). This is
partially driven by an increase in the AUM of Nikkei 225 volatility ETNs. These ETNs typically replicate the returns from
daily rolling long positions in the VNKY futures contracts. The daily rolling of VNKY futures positions (selling 1 st month
contracts and buying 2nd month contracts) has an impact of steepening the term structure at the short end and hence
richening the roll cost. With such ETNs AUM reaching USD 50mn (~USD 2.0mn vega) and low realized volatility, we
witnessed a record level of VNKY roll cost in 3Q14 (Figure 31), although it came off rapidly in October amid the BoJ
driven market rally and consequent spike in VNKY. As shown in the case of VIX, a further increase in the size of Nikkei
long volatility ETNs may put a downward pressure on the front end of the volatility curve and hence lead to more upward
sloping term structures on the front end when the Nikkei 225 volatility normalizes.
Figure 30: VNKY futures level and open interest
# of contract (‘000)
Source: J.P. Morgan, Bloomberg.
Figure 31: Nikkei volatility futures open interest and roll cost
Index Level
AUM (USD Mn)
% Roll cost
*Monthly roll cost defined as spread between 1st and 2nd VNKY futures (as % of futures level)
On a separate note, VKOSPI futures were just launched in November 2014 with relatively better initial turnover compared
to the cases of VHSI and VNKY – the growth of VKOSPI futures and its potential impact on the volatility curve may be
worth investors' attention.
15
Marko Kolanovic
(1-212) 272-1438
15 December 2014
Going into 2015, we expect the demand for structured products for yield to remain strong in the prolonged low interest
environment, putting continued pressure on the back end of the vol curve. However, we find more risk factors that may
drive realized volatility higher from the post GFC-low levels and hence lead to higher short dated volatility and flatter term
structure than what we observed in 2014. Even though Japan is officially in recession after 2 quarters of negative real GDP
growth in 2Q and 3Q 2014, the reduced policy uncertainty on the back of the fresh stimulus from Bank of Japan and the
delay of 2nd consumption tax hike should steer term structure clear of inversion risks. However, we see the risk of term
structure inversion to resurge in Nikkei 225 if the confluence of disappointing data and inactions of Bank of Japan repeat in
2015. For China, while we anticipate easing measures to reduce market stress, we see the timing of People Bank of China’s
policy actions and prospects of China’s economic growth as risk factors for short-lived term structure inversions in Hshares. We also see higher risks for Hang Seng and ASX 200 as the Fed’s shrinking balance sheet is set to weigh more
heavily on these markets in our view.
16
15 December 2014
Marko Kolanovic
(1-212) 272-1438
Skew
Global index skews were relatively stable in the first half of the year, exhibited only a modest spike as a result of risk
aversion during the September/October sell-off, and then re-priced lower as equity markets recovered. At the time of
writing, index skews in US and Europe were marginally higher than the levels at the start of the year, while Asian index
skews all decreased, despite the fact that US and Europe skews started from a higher base. This divergence reflects the
difference in volatility supply and demand dynamics across the regions. The highest absolute level of 6M 90%-110% skew
belongs to the S&P 500, while H-shares sits at the opposite end of the spectrum with its OTM call volatility higher than put
volatility.
Figure 32: Skews steepened in the US but remained largely
suppressed in Asia in 2014
6M 90%-110% skew
Table 5: Summary of 6M skews across the globe – sorted by current 6M
90%-110% skew spread
6M 90-110%
5Y
Skew
Current
%il e
Avg
Max
Min
SPX
7.6%
55%
7.6%
9.5%
5.3%
UKX
6.3%
37%
6.8%
9.7%
4.4%
AS51
6.1%
72%
5.6%
7.7%
3.8%
SMI
5.7%
57%
5.5%
7.5%
3.3%
DAX
5.4%
4%
6.5%
9.6%
5.1%
SX5E
4.5%
3%
6.2%
10.0%
4.3%
NKY
2.1%
33%
3.8%
9.8%
0.1%
KOSPI2
1.4%
1%
3.9%
7.9%
1.4%
HSI
0.5%
0%
3.5%
8.1%
0.5%
HSCEI
-0.9%
0%
2.9%
8.1%
-0.9%
* Data as of December 5, 2014
US: With 2014 market performance on pace for another double digit % gain, S&P 500 volatilities spent most of the year in
a ‘sticky-delta’ regime; i.e. where fixed delta implied volatilities remained stable, as opposed to fixed strike volatilities
holding steady and fixed delta vols sliding along the skew.
Figure 33: S&P 500 skew as a % of ATM volatility levels reached alltime highs this summer...
Figure 34: … driving S&P 500 levered risk reversals to record
leverage levels
90%
8.0
80%
7.0
70%
6.0
60%
5.0
4.0
50%
3.0
40%
30%
20%
Jan-12
SPX 6M 90-110% Risk Reversal
Leverage Ratio
Jul-12
Jan-13
Jul-13
3M 90-110 Skew/ATM Vol
2.0
6M 90-110 Skew/ATM Vol
1.0
Jan-14
Jul-14
0.0
Jan-12
Jul-12
Jan-13
Jul-13
Jan-14
Jul-14
S&P 500 skew generally steepened this year and reached record levels as a % of volatility in Q3 (Figure 33); hedging
demand was robust (albeit mostly with far OTM options), and overwriting remained a popular strategy to generate yield
with rates still low. The combination of steep skew, low implied volatility levels (which continued to be weighed down by
low realized volatility as the market grinded higher), and low rates (which keeps the forward low vs. spot) drove the
17
15 December 2014
Marko Kolanovic
(1-212) 272-1438
leverage available on S&P 500 costless risk reversals to all-time highs in early summer. For example, the leverage available
on a costless 6M 90-110% risk reversal (i.e. sell one 6M 90% put to buy a multiple of 110% calls for zero net premium)
reached all-time highs above 7x (Figure 34). However, following October’s brief but sharp market selloff, implied volatility
levels shifted higher and skew flattened, significantly reducing the leverage ratios on these structures. The skew flattening
post-Oct was particularly pronounced for OTM calls; call wing volatilities reset higher as investors re-priced the likelihood
of a sharp rally, after the S&P 500 rallied ~10% in just 1 month.
Contributing to the steep skew is the fact that the S&P 500 put/call ratio surged and reached record highs this year, yet most
of the outstanding puts are struck far out-of-the-money. During the last cycle, the average put strike crept higher as
volatility fell, allowing investors to buy closer to ATM puts for a constant hedging budget. However, this cycle, the average
put strike stayed relatively constant and was further OTM on average than last cycle (~20% OTM on average vs. ~13%
OTM in 2004-7) as hedgers maintained mostly crash protection (Figure 36). By contrast, calls were struck at similar levels
on average this cycle and last (slightly under 2% OTM on average), but have been struck less and less OTM over the course
of the current cycle, likely as a consequence of the declining levels of volatility which force overwriters to sell calls closer
to the money in order to generate a particular premium level. This indicates that volatility sellers have become increasingly
aggressive to generate yield.
Figure 35: The SPX put/call ratio surged to a record this year, due to
both an increase in puts and a decrease in calls outstanding
Figure 36: Average call moneyness is little changed this cycle vs.
last, but puts are struck on average ~7% further OTM
S&P 500 Level
Open interest weighted average moneyness for S&P 500 options
Put/Call Open Interest Ratio
2200
2000
2.3
2.2
2.1
2
1.9
1.8
1.7
1.6
1.5
1.4
1.3
SPX Index
1800
Put/Call Ratio
1600
1400
1200
1000
800
600
2009
2010
2011
2012
2013
2014
120%
115%
110%
105%
100%
95%
90%
85%
80%
75%
70%
2004
Avg Call Moneyness
Avg Put Moneyness
2006
2008
2010
2012
2014
The continued demand for mainly far OTM protection and selling of short-dated ATM/slightly OTM calls are also evident
in the current skew surface. Figure 37 below shows a heatmap depicting the relative richness of various points along the
S&P 500 implied volatility surface, based on their 2-year percentiles (i.e. over the recent low volatility period). Deep OTM
put wing volatilities are relatively expensive, mostly in their highest quartile relative to the last 2 years, while short-dated
close to the money and longer-dated OTM call wing vols appear relatively cheap.
Figure 37: S&P 500 skew surface richness (2Y percentiles)
Tenor 70
75
1M
2M
3M
6M
0.80
1Y
0.76 0.74
2Y
0.77 0.76
80
0.78
0.76
0.72
0.75
85
0.64
0.67
0.70
0.71
0.67
0.72
90
0.53
0.58
0.62
0.66
0.61
0.69
95
0.32
0.45
0.50
0.58
0.55
0.66
18
Strike
100
0.14
0.28
0.32
0.51
0.47
0.62
105
0.36
0.36
0.37
0.47
0.44
0.55
110
0.66
0.47
0.48
0.46
0.42
0.50
115
0.70
0.48
0.51
0.54
0.38
0.45
120
125
130
0.51
0.55 0.55
0.36 0.36 0.37
0.40 0.35 0.31
15 December 2014
Marko Kolanovic
(1-212) 272-1438
We expect the same skew drivers to largely remain in place heading into 2015, keeping S&P 500 skew as one of the
steepest among global indices. The deep liquidity in S&P 500 options, coupled with the fact that US equities represent
~50% of the MSCI AC World basket, is likely to continue to drive strong demand for S&P 500 puts for hedging global
risky asset portfolios. Additionally, although the Fed is expected to begin rate hikes next year, rates will remain historically
low (our Rates Strategists expect the 10Y yield to rise only to 2.8% by 2015 YE) and thus keep investors searching for yield
- this is likely to drive continued interest in call overwriting strategies, which steepen the S&P 500 call wing skew.
Europe: Shorter-dated skew across most European indices on average steepened in 2014, while longer-dated skews
flattened (Figure 38). The largest steepening relative to last year was observed for the FTSE 100 skew, which experienced
dynamics closer to the S&P 500 than to the rest of Europe and was also impacted by uncertainty around the Scottish
elections. We think that the FTSE skew is likely to remain steep in 2015, as demand for hedges persists and investors focus
on the potential impact of the UK elections in May.
Interestingly, the behavior of the Euro STOXX 50 long-dated skew in 2014 was very similar to that of Asian index skews,
which we attribute mostly to the continued issuance of downside-volatility selling structured products as investors kept
seeking yield in a range bound equity market. We find it attractive to be long longer-dated Euro STOXX 50 skew into next
year as a way to hedge, not only because it has reached historical lows and looks cheap relative to S&P500 and FTSE
long-dated skews (Figure 39), but also as we expect it to react strongly in a sharp correction, despite the fact that it would
not perform in a smaller correction due to the structure product hedging dynamics.
Figure 38: European shorter-dated skews were mostly steeper over
the year while longer-dated were flatter
Figure 39: Euro STOXX 50 longer-dated skew has reached historical
lows and is looking cheap, in our view
Volatility points
2Y 90-110% skew (vol points
SX5E
Dec-14
Jul-14
Feb-14
Sep-13
Apr-13
Nov-12
Jun-12
Jan-12
Aug-11
Mar-11
Dec-09
1%
FTSEMIB
-1.0%
SX7E
2%
DAX
-0.5%
IBEX
3%
SX5E
0.0%
SMI
4%
UKX
0.5%
SPX
5%
Oct-10
1.0%
UKX
6%
May-10
Change in avg. 3M 90-110 Skew 2014-2013
Change in avg. 2Y 90-110 Skew 2014-2013
1.5%
The long-dated skew seems to be dislocated from other related market indicators. For instance, the dividend term structure
fell precipitously during the October correction, at the same time as long-dated skew. The rapid equity sell-off led to both a
supply of long dated dividends as well as a flattening pressure on the long-dated skew, as a result of the hedging for retail
structured products. However, the dividend term structure has since recovered, whereas long dated skew hasn’t (Figure 40).
19
15 December 2014
Marko Kolanovic
(1-212) 272-1438
Figure 40: SX5E Skew and dividend term structure de-coupled after
the October sell-off
Figure 41: Comparison between SX5E implied skew and 6M put
spread max payoff to cost ratio
Standardized skew
Implied skewness of return distribution
Dividend Term Structure
Max Payoff/Cost Ratio (times)
2.0
25.0%
-19
-21
-23
-25
-27
-29
-31
-33
-35
22.5%
20.0%
17.5%
Nov-14
Oct-14
Sep-14
Aug-14
Jun-14
May-14
15.0%
Jul-14
Standardized Skew Level
Dividend Term Structure
5.0
6M Implied Skew (LHS)
1.5
6M ATMF/90% Fwd PS payoff/cost
4.0
1.0
3.0
0.5
0.0
2.0
2005 2006 2007 2008 2009 2010 2011 2012 2013 2014
What does the flat skew mean to us and how can we monetize the dislocation? In a previous report, we showed that the
standardized skew, which is the 95-105 skew divided by the ATM volatility, closely proxies the skewness (standardized
third moment) of the implied return distribution. Moreover, they also serve useful economic purposes, as standardized skew
is a good indicator for the pricing of put spreads. Therefore, we prefer to buy put spreads on indices with high standardized
skews. In the trade idea section, we suggest buying put spreads on FTSE to hedge the political uncertainty in 2015.
Table 6: Skew level and percentile for global indices
Index
SPX Index
UKX Index
SMI Index
AEX Index
OMX Index
DAX Index
CAC Index
TOP40 Index
SX5E Index
EEM UP Equity
IBEX Index
XU030 Index
FTSEMIB Index
WIG20 Index
RDXUSD Index
NKY Index
HSI Index
HSCEI Index
6M 95/105% skew
standardized by ATM vol
28.3%
25.5%
22.7%
19.1%
19.1%
16.1%
15.5%
15.3%
13.8%
13.5%
10.6%
8.4%
8.0%
7.4%
7.1%
3.8%
0.9%
-2.0%
Skew percentile
(since 2005)
92.4%
84.9%
92.4%
74.6%
90.4%
40.8%
44.8%
45.2%
30.2%
82.7%
20.2%
56.3%
1.0%
29.7%
36.4%
23.1%
0.0%
0.3%
Figure 42: Call away ratio is correlated with implied skew
Call away ratio
80%
DAX
SPX
OMX
RTY
AEXSMI
CAC AS51 UKX
SX5E
y = 1.0515x + 0.4257
R² = 0.5553
70%
60%
NKY
HSI
FTSEMIB
50%
EEM
IBEX
40%
5%
10%
15%
20%
25%
30%
35%
3M standardized skew
We also show that standardized skew can be useful for identifying call overwriting candidates. Specifically, we show that
indices with flat skew tend to be called away less than those with steep skews. We find the same observations on single
stocks as well. Liquid Euro indices tend to have average skew compared to other global indices. However, since we see a
macro environment of rising volatility in 2015, we suggest overwriting on a more discriminate basis, and propose a
methodology to reduce the call away ratio. On the other hand, EEM has been a good call overwriting candidate in 2014,
where we have witnessed a precipitous decline in correlations among EM equities. This will likely continue to be the case in
2015, as our global Equity Strategists are OW Asia and UW Latam and CEEMEA. The expected divergence in EM returns
would make EEM a good underlier for call overwriting, as well as a good funding leg in call switch trades with selective
EM countries (within EM we are OW China, India, Mexico, and Turkey).
20
Marko Kolanovic
(1-212) 272-1438
15 December 2014
Asia: Asian index skews remained largely suppressed, decoupling from other regions. While active structured product
issuance (Figure 29) continued to suppress downside volatility 8, strong upside demand from institutional investors as well as
retail investors supported upside volatility. On the back of excitement around the Shanghai-Hong Kong Stock Connect,
investors positioned for upside exposure in China (both onshore and offshore) via a range of exchange listed products,
including ETFs, futures, warrants and options. Retail warrants issuance in Hong Kong increased significantly in 2H14,
outweighing the pace and magnitude of structured products issuance and hence resulting in volatility expansion and
suppressed skews (Figure 43 and Figure 44).
Figure 43: Retail warrants issuance in Hong Kong increased in 2H14
due to excitements around the Stock Connect
Figure 44: Strong demand for China exposure was shown in increased
flows in China related derivatives and a pronounced H-shares smile
Vega issuance (USD mn)
Asset under management (USD Bn)
HSI index level
Source: J.P. Morgan, Bloomberg. * Monthly data up to Oct 2014. Warrants issuance estimated
based on the data provided by HKEx and structured product issuance estimated based on the
data complied by JPM marketers.
Skew spread
In Japan, the upside demand via derivatives vehicles retreated in 2014, as the listed index call open interest notional was
~20% lower on average than the aggressive levels in 2013. Still, we observed a few spot -up & volatility-up phenomena of
smaller magnitude in Nikkei 225 this year, driven by structured product issuers who bought back vega to rebalance their
hedges, as knock-out features embedded in the products were triggered as the underlying index rose (Figure 45). Hence, the
correlation between the spot and implied volatility remained much less negative (or even positive) for the Asian indices with
active structured products markets, namely Nikkei 225, H-shares and KOSPI 200 (Figure 46).
Going into 2015, despite the uncertainties around Fed tightening remaining one of the major risks to support skews globally,
aggressive policy support in Asian countries (as shown in the recent RRR cut by the People's Bank of China and additional
easing from the Bank of Japan) should help to alleviate concerns on economic growth and structural issues and hence keep
Asian skews suppressed overall versus other regions. Other positive macro drivers in China and Japan, such as further
development around the Stock Connect or and GPIF reform, may keep upside skews expensive, again providing
opportunities to extract upside volatility richness through barriers and call spreads/ratios. The continued popularity of retail
structured products in Asia is likely to put pressure on downside skews in KOSPI 200, H-shares and Nikkei 225.
8
Structured products in Asia are predominantly volatility-selling in nature, where the coupon is funded from the selling of put options often
with exotic barrier features. The significant growth of this market has led to an imbalance of volatility supply and demand; as the product
issuers hedge their long vega exposure, they suppress market volatility and skew. For details, see “Asia Pacific Equity Derivatives Weekly
Highlights”, Tony Lee, 16-Apr-2012.
21
15 December 2014
Marko Kolanovic
(1-212) 272-1438
Figure 45: Structured product aggregate vega outstanding estimates
for Nikkei 225, KOSPI 200 and HSCEI
Vega (USD mn)
Figure 46: Correlation between spot and volatility moves remained
largely positive for Nikkei 225 and H-shares but slightly negative for
KOSPI 200 which failed to break out of its multi-year trading range
12M correlation between 12M ATM vol moves (ex-skew) and spot moves
Spot Moves (%)
Source: J.P. Morgan, Bloomberg. * Spot levels as of December 5, 2014. Estimated based on the
monthly issuance data up to October 2014. Japan issuance data is based on the public issuance
only and therefore may not represent an accurate picture. Private placements can be 1~1.5 times
larger in notional.
As macro drivers tend to have a significant impact on the direction and volatility across different asset classes, monitoring
their relationships can help investors take advantage of any dislocation opportunities. For example, the relationship between
USDJPY and Nikkei 225 and that between H-shares and USDCNY have been well documented. USDJPY and Nikkei 225
have historically exhibited a highly positive correlation, which has been reinforced by Abenomics and Bank of Japan easing
policies over the past few years (Figure 47). Currently, a regression analysis implies a slight richness in Nikkei 225 calls vs.
USDJPY calls, although the dislocation is not large enough to trigger relative value trading opportunities.
On the other hand, USDCNY and H-shares have exhibited a negative correlation, as concerns of a hard landing or growth
slowdown tend to be reflected in both negative equity market performance and currency weakness due to capital outflows
(Figure 48). Hence, investors have been using H-shares puts and/or USDCNY call options for tail risk hedging purposes.
While the volatilities of the pair have shown further divergence after China double d the CNY trading band, prolonged
periods of USDCNY weakness could signal equity market stress. With the depressed levels of H -shares downside volatility
from ongoing structured product issuance, we continue to prefer going short H-shares put ratios as a tail risk hedge.
Figure 47: Nikkei 225 call implied volatility remains highly correlated
with USDJPY call implied volatility due to BoJ policy actions
Nikkei 225 volatility
Figure 48: Correlation between H-shares put implied volatility and
USDCNY call implied volatility weakened after fx trading band widening
USDJPY volatility
35%
20%
30%
17%
25%
14%
20%
USDCNY volatility
70%
6%
Doubling of trading
band of CNY on March
15 led to expectation
of rising 2-way price
60%
5%
50%
4%
40%
3%
30%
2%
11%
15%
8%
Nikkei 225 3M 25D Call Volatility
USDJPY 3M 25D Call Volatility
10%
Dec-09
Dec-10
Dec-11
22
HSCEI volatility
Dec-12
Dec-13
5%
Dec-14
20%
1%
H-shares 3M 25D Put Volatility
USDCNY 3M 25D Call Volatility
10%
Dec-09
Dec-10
Dec-11
Dec-12
Dec-13
0%
Dec-14
15 December 2014
Marko Kolanovic
(1-212) 272-1438
Implied Correlation
As we explained in the Outlook for Equity Risk section, most volatility premia contracted recently. One that stayed rich
though is the premium of index options vs. single stock options volatility, i.e. implied correlation. However, the elevated
levels of this premium may be fair given the risk of correlation spikes we mentioned in the introduction.
US: Implied correlation levels on the S&P 500 generally trended higher during most of this year, albeit from the low levels
in 2013, and continued to trade at a significant premium to realized correlation levels (Figure 49). Average implied
correlation levels in 2014 were slightly higher and realized correlation levels close to in line with 2013, keeping the average
implied-to-realized correlation spread at its widest in 10 years. Implied correlation continued to trade rich due to the
S&P 500 index implied volatility premium and cheap single stock volatilities (as highlighted in Figure 7). Figure 50 shows
the term structure of implied correlation, which steepened significantly this year, reflecting the steep S&P 500 term
structure discussed in the Term Structure section. This indicates the relatively strong demand for longer dated (e.g. ~1Y)
index volatility for hedging, and greater willingness of investors to sell shorter-dated index volatility for yield.
Figure 49 : S&P 500 implied correlation traded at a 10-year high
premium to realized in 2014
90%
80%
70%
60%
50%
40%
30%
20%
10%
0%
2004
Figure 50: The term structure of correlation steepened significantly
this year, particularly out to ~1Y tenor
50%
Correlation Carry (right axis)
1Y Implied Correlation
6M Realised Correlation
40%
30%
S&P 500 implied correlation spread
20%
1Y-3M Correlation Spread
2Y-1Y Correlation Spread
15%
20%
10%
0%
10%
5%
-10%
2006
2008
2010
2012
2014
0%
Jan-12
Jul-12
Jan-13
Jul-13
Jan-14
Jul-14
Our Oct 15th Volatility Review highlighted a spike in implied correlation which drove the spread between index and single
stock volatilities to ~4-year lows and presented an attractive opportunity to go long this spread by trading S&P 500 vanilla
dispersion. As the market recovered in a “V” shape, implied correlation fell rapidly and widened this spread. Although less
attractive than in October, we continue to favor trading vega weighted SPX dispersion as an efficient way to gain long
volatility exposure, and since the implied spread remains well below the realized spread over the last couple of years.
Additionally, we continue to favor exploiting the high premium of implied correlation by biasing long volatility strategies to
be implemented primarily through single stock rather than index options.
Europe: European implied correlation trended higher during 2014, and picked up pace during the October correction which
led them to reach their taper tantrum highs. Expectations for the announcement of Sovereign QE will contribute to keep
implied correlation elevated in the first part of the year, while correlation might subsequently decline as markets revert to
focusing more on fundamentals.
In 2014, the average European index implied-to-realised correlation spread was close to its 2013 levels. We think that the
correlation risk premium will likely be high in 2015, partly because the current low volatility environment makes it
relatively riskier to monetize the spread directly. Throughout 2014, earnings seasons led to substantial dispersion in stock
performance and were crucial in lowering realised correlation, a behavior which we think will likely continue in 2015.
23
15 December 2014
Marko Kolanovic
(1-212) 272-1438
Figure 51: European implied and realized correlations reached 2013 Figure 52: Euro STOXX 50 1M realised correlation hit its YTD lows in
highs in the October correction and remain elevated heading into 2015 the Q2 earnings season and has followed 6M realised higher since
Avg implied and realised correlation across European indices*
Avg 6M implied
0.80
Avg 6M realized
Correlation
Avg 1M realized
Euro STOXX 50 6M Realised Correl
Euro STOXX 50 1M Realised Correl
0.80
0.70
0.60
0.60
0.50
0.40
0.40
0.30
Oct-14
Apr-14
Jan-14
2014
2013
2012
2011
2010
Source: J.P. Morgan Equity Derivatives Strategy. * Euro STOXX 50, FTSE, DAX and SMI. As of
12-Dec-2014.
Jul-14
0.20
0.20
On top of the earnings season induced dispersion, we think that 2015 will also see substantial de-correlation from sector and
stock rotation, especially in H2-15, following a first half of the year which might be more macro/central bank driven. The
strong performance divergence between European Cyclicals and Defensives, with the YTD outperformance of Defensives
peaking at around 19% at the height of the correction in October (Figure 53), is set to retrace as economic activity picks up
in the Euro area, in our Equity Strategy team’s view. Dispersion amongst European sector indices was also elevated in
2014, with Health Care and Utilities up by 19.7% and 14.8%, respectively, and Oil & Gas, Basic Resources and Retail down
by 15.6%, 10.2%, and 7.9%, respectively.
Figure 53: European Defensives significantly outperformed Cyclicals Figure 54: European sector performance has been mixed YTD
in 2014
Oil & Gas
Basic Resources
Retail
Industrial Goods
Banks
Construction & Material
Autos
Chemicals
Technology
Media
Financial Services
Personal & Household Goods
Insurance
Telecoms
Food & Beverage
Travel & Leasure
Utilities
Health Care
YTD outperformance
20%
Defensives vs Cyclicals
16%
12%
8%
4%
03-Dec
05-Nov
08-Oct
10-Sep
13-Aug
16-Jul
18-Jun
21-May
26-Mar
26-Feb
29-Jan
01-Jan
-4%
23-Apr
0%
-20%
Year-to-date Total
Return
-10%
0%
10%
20%
30%
Asia: Across the major indices, implied correlations started the year on a declining trend but picked up as soon as market
specific catalysts emerged, such as the Shanghai-Hong Kong Stock Connect and the surprise monetary easing from BoJ. On
the other hand, realized correlations have generally fallen (Figure 55) with ASX 200 (Top 15) and Hang Seng (Top 15) 6M
realized correlations dropping to the 39th and 23rd percentiles versus their 3Y histories, while TOPIX Core 30 (versus
Nikkei 225) correlation remains relatively high (68th %ile compared to its 3Y history).
Implied correlations remain high compared to realized, but low levels of volatility have made it increasingly difficult to
capitalize on this. To illustrate this point, we can look at the index weighted dispersion trade performance for ASX 200, a
24
Marko Kolanovic
(1-212) 272-1438
15 December 2014
market with tradable volatility swap dispersion. The implied correlation richness is driven by abundant single-stock
volatility supply from overwriting activities, in addition to index protection demand from investors using ASX 200 as a
proxy hedge to both developed markets and China, with lower volatility. The spread between 6M ATM implied correlation
at the middle of May and that realized in the subsequent 6M period was over 24 correlation points – the widest this spread
has been over the last year and a half. However, low volatility suppressed returns to ~2.0 volatility points (pre-bid/offer) for
a 6M ASX 200 (Top 15) dispersion trade starting at the end of May (Figure 56). Had the move in correlation been the same,
but with single stock volatilities moving to their 3Y average of 18% rather than the actual value of 15%, the profit from the
same dispersion trade would have been much higher at ~3.8 volatility points (pre-bid/offer).
Figure 55: Realized correlations across Asia have fallen this year
although TOPIX Core 30 remains relatively high
Figure 56: Returns on index-weighted 6M dispersion for ASX 200
suppressed by low levels of volatility
6M realized correlation
Correlation spread
90%
Dispersion P&L (volatility points)
50%
5%
40%
4%
70%
30%
3%
60%
20%
2%
50%
10%
1%
40%
0%
0%
30%
-10%
80%
ASX 200 (Top 15)
Hang Seng (Top 15)
TOPIX Core 30 (versus Nikkei 225)
20%
Dec-11
Jun-12
Dec-12
Jun-13
-1%
Implied to Subequent Realized Correlation Spread
Index Weighted Dispersion P&L
Dec-13
Jun-14
Dec-14
-20%
Dec-11
Jun-12
Dec-12
Jun-13
Dec-13
Jun-14
-2%
Dec-14
In Hong Kong, positioning ahead of the Shanghai-Hong Kong Stock Connect program was a significant driver of market
direction as well as correlation. Since the announcement, investors established bullish positions via index products, which
resulted in incremental upward pressure on correlation. Index correlation rose further on the broad based market rally after
the People’s Bank of China surprised market participants with an interest rate cut (Figure 57). In Japan, we observed wider
stock performance dispersion and lower correlation in the first eight months of the year, driven by strong corporate profits
and earnings momentum, as well as relatively light index-based product positioning by macro and foreign investors.
However, policy actions from the Bank of Japan and catch-up positioning in Nikkei 225 following the sharp deprecation of
the Yen again resulted in a sharp pickup in TOPIX Core 30 correlation (Figure 58).
25
15 December 2014
Marko Kolanovic
(1-212) 272-1438
Figure 57: Bullish positioning through Hang Seng futures ahead of
Shanghai-Hong Kong Stock Connect drove correlation higher
Figure 58: US dollar strength and expectation of further BoJ easing
drove USDJPY and TOPIX Core 30 correlation higher
3M realized correlation
3M correlation
70%
60%
Hang Seng futures open interest
Hang Seng 3M Realized Correlation
Hang Seng Futures Open Interest (3M Moving Average)
Annoucement of ShanghaiHong Kong Stock Connect
on April 10th
50%
100%
140
145,000
90%
130
140,000
80%
135,000
70%
130,000
60%
125,000
50%
120,000
40%
115,000
30%
120
110
100
40%
30%
20%
Dec-12
Jun-13
Dec-13
USDJPY
150,000
Jun-14
110,000
Dec-14
90
TOPIX Core 30 3M ATM Implied Correlation
TOPIX Core 30 3M Realized Correlation
USDJPY
20%
Dec-12
Jun-13
Dec-13
Jun-14
80
70
Dec-14
Looking forward to 2015, although our equity strategist is bearish on China growth, we see the potential for further easing
and stimulus from policy makers in reaction to weak economic data as the key driver of higher correlation for Hang Seng.
We already witnessed an example in November of a highly correlated rally resulting from an earlier than expected interest
rate cut. The growth momentum may continue to face downside risk in the near term but may pick up in 2Q15 and 3Q15
due to the impact of policy support. Our economist is forecasting two RRR cuts in 2015. As investors pre-position and
anticipate the next set of policy moves, the equity sentiment and direction will remain driven by macro factors, keeping
correlation at an elevated level.
For TOPIX Core 30, with Japan officially moving into a recession after two quarters of negative GDP growth, the
conventional thinking would be that this type of macro shock would lead to a higher volatility regime which keeps
correlation elevated. However, the poor economic data is already well expected by market participants as a result of the
consumption tax hike, and Prime Minister Abe's snap election in December is the remaining macro event in the near term.
In 1H15, investors will shift their attention to earnings results for FY15 year end in March, along with wage negotiations
and shareholder friendly corporate actions such as share buybacks and dividend increases, which should result in a lower
correlation environment.
For ASX 200, the structural volatility supply and demand dynamics will continue to be a main driver of implied correlation
richness, while market structure and micro drivers will provide support for a stable low realized correlation environment.
Financials, staples and telecom companies make up 60% of the index and these domestic companies tend to have steady
earnings histories and high yields. Low rates support these sectors but neither valuation nor earnings have significant upside
potential. Materials and energy groups are challenged by a weak price background and the other sectors are quite fully
valued, according to our strategist outlook for the year ahead.
Despite the implied correlation richness, we have seen reluctance from investors to enter into short correlation positions on
ASX 200, as its implied correlation has traded below the psychologically important level of 0.60. However with realized
correlation trading well below this level – biased to fall further, in our view – we think short correlation trades still have
good positive carry and can continue to offer value. As implied correlation and volatility remain at unattractive levels for
shorting, and relatively high bid/offer spreads erode returns in practice, investors may have to choose their timing carefully
to enter into correlation trades, using any volatility and correlation spikes as an opportunity for selling correlation. These
may occur as a result of potential growth shocks from China. In terms of vega weighting, investors can consider equal vega
notional for implementing the dispersion trade. This vega weighting setup allows for short correlation while being long
volatility at the same time. With volatility at multi-year lows, this strategy can also be used as an efficient way to own
volatility, in effect using the alpha available from short correlation to subsidize the cost of being long volatility.
26
15 December 2014
Marko Kolanovic
(1-212) 272-1438
Implied Dividends
Euro STOXX 50 Dividends
Performance review: The front-end dividends are on track to delivering small positive returns for 2014 (Figure 59).
Technical factors such as the Total SA ex-dividend dates aside, the performance is below our initial forecast made a year
ago. Concerns over weak economic growth and deflation have been the main contributor to this underperformance, in our
view. However, as seen in Table 7, for the third year in a row, the front end dividends have outperformed equities on a beta
adjusted basis. Historically, we observe a beta of 0.4 for like maturity equivalents of the 2016s and 0.6 for the 2017s.
Figure 59: 2014 year-to-date total returns across related asset
classes
Table 7: Historical returns of SX5E dividend futures and related asset
classes
% YTD return
10%
7.2%
4.0%
5%
2.7%
2.4%
1.6%
1.4%
JPM Euro BB
JPM Euro B
JPM Euro CCC
DEDZ +1Y
DEDZ +2Y
DEDZ +5Y
SX5T
YTD
7.2%
4.0%
4.1%
2.4%
1.4%
-3.7%
1.6%
2013
8.4%
12.6%
15.4%
10.3%
13.4%
12.4%
21.5%
2012
20.1%
28.7%
37.4%
14.9%
15.7%
18.3%
18.1%
2011
5.2%
-1.5%
-9.4%
-3.3%
-14.0%
-22.0%
-14.1%
Source: J.P. Morgan, Bloomberg, Return of dividend futures include 1Y Euribor swap yield. As
of 12-Dec-14
0%
-5%
€ BB
€B
-3.7%
€ CCC DEDZ5 DEDZ6 DEDZ9 SX5E
TR
Source: J.P. Morgan, Bloomberg, Return of dividend futures include 1Y Euribor swap yield. As
of 12-Dec-14
Looking into 2015, our outlook for both the equity and credit markets are relatively sanguine, anchored by the ECB’s
balance sheet expansion. In our view, ECB policies are likely to usher in a renewed period of search for yield, which should
benefit carry instruments such as short-dated dividend futures. In particular, we see value in dividends relative to both
equities and HY credit.
Figure 60: Estimates for next year dividends have been continually
revised down since 2008, but are showing signs of bottoming
Figure 61: SX5E DPS growth estimates are modest compared to EPS
YoY growth rate
Index dividend level
200
IBES EPS Est
2009
2008
150
10.9% 10.4%
JPM Dvd Est
2007
2012
2010
2011
2006
100
IBES Dvd Est
6.5%
20132014 2015
10.5%
7.7%
6.1%
3.2%
1.7%
2005
-0.5%
15E
'14
'13
'12
'11
'10
'09
'08
'07
'06
'05
14E
'04
50
16E
Fiscal year estimates
Fundamentals are solid. As Figure 60 illustrates, 2013 likely marked the bottom of the post-2008 dividend payout (109.8
index points). More importantly, the negative momentum of downward revisions in dividend estimates has come to an end.
Although it is perhaps too early to predict an upswing in dividend payouts similar to the pre-2008 period, consensus
27
Marko Kolanovic
(1-212) 272-1438
15 December 2014
estimates have stabilized and companies’ dividend announcements have shown tendencies to surprise on the upside. We are
comfortable with our bottom up estimates for the 2015 – 2017 calendar years. As Figure 61 shows, the dividend growth
estimates are conservative relative to EPS growth estimates. Oil companies account for 12% of the dividend estimates
(mainly from TOTAL), but the risks should be relatively contained given our outlook on oil price and TOTAL's balance
sheet strength.
Moreover, we believe the current economic environment favours dividend payouts. European corporates (ex-financials)
maintain record high cash on their balance sheet (Figure 62), against a backdrop where leverage is already near an all time
low. The combination of low yield, low growth, high cash balance, and low leverage, suggest a cash return to shareholders
is the most feasible action by the corporates. Therefore, we do not find the lower DPS growth estimates justified.
Figure 62: MSCI Europe ex Financials cash on balance sheets
Source: J.P. Morgan Equity Strategy, Worldscope
At the same time, the 16s and 17s offer higher expected returns compared to Euro HY bonds (Figure 63). Given the
solid fundamentals as we outlined above, we believe they are an appealing alternative for yield, and a good way to diversify
for credit investors.
Figure 63: Expected return comparison between Euro HY and dividend futures
JPM Euro HY Index Statistics
Avg Maturity (Yrs)
Annual Req Return / Spread (bps )
BB
4.7
264
B
4.8
622
Div '15 Div '16 Div '17
1.0
2.0
3.0
190
782
870
In the base case, we forecast a 2015 return of 8.5% for the 16s and 10.4% for the 17s. This compares with our forecasts of
13% expected return for MSCI Eurozone and 4.6% for European HY credit. Adjusting for the expected beta, short dated
dividends should continue outperforming equities, in our view.
Long dated dividend term structure: As we have demonstrated (see Revisiting SX5E Dividend Steepeners), there is a
direct relationship between the yield gap (long dated bond yields – index dividend yield) and the slope of the SX5E
dividend term structure. The yield gap has become even more pronounced, with lower bond yields and higher dividend
yield. The relative pricing does not suggest any cheapness in the dividend term structure steepener. Moreover, as Table 7
has shown, long dated dividends tend to underperform on a risk adjusted basis in up as well as down years. Therefore, we
do not find them attractive at the current pricing.
28
15 December 2014
Marko Kolanovic
(1-212) 272-1438
FTSE 100 Dividends
FTSE 100 dividend futures are on track to end the year approximately flat, their weakest yearly performance since 2011.
2014 saw two distinct regimes for FTSE dividend futures, with steady gains across the curve and low volatility in the first
half of the year, followed by weakness in the second half of the year which erased all of the year’s gains (Figure 64).
Figure 64: The FTSE dividend futures are set to end the year
approximately flat
Year to date performance of FTSE 2015 and FTSE 2016 dividend futures
8%
Upside to bottom-up FTSE 100 dividend estimates
FTSE '16 div futures
FTSE '15 div futures
6%
Figure 65: The upside of FTSE dividends to JPM and IBES
consensus estimates is comparable with that for Euro STOXX 50, but
Euro STOXX 50 dividends offer better risk reward in our view
20%
18.0%
14.9%
15%
4%
2%
12.8%
9.5%
10%
0%
-4%
0%
Dec-14
Jun-14
Mar-14
Dec-13
Sep-14
-2%
5%
3.5%
5.4%
FTSE 2015
FTSE 2016
Potential upside vs JPM Estimates
FTSE 2017
Potential upside vs IBES Estimates
A combination of declining implied dividend levels and a weakening of the British Pound relative to the US Dollar in H214 led to an improvement in the upside to bottom-up estimates across the curve. Despite an expected upside of 9.5% for the
’16 contracts and 14.9% for the ’17s relative to JPM bottom-up estimates (Figure 65), the picture for FTSE dividends
remains mixed. While we expect positive returns over the year from the '16 and ’17 contracts, we find that the risk-reward
of Euro STOXX 50 contracts is superior. In our view, the positive impact from a likely continued weakness of the British
Pound relative to the US Dollar is more than offset by the risk originating from the high exposure of FTSE 100 dividends to
oil and commodity prices, with ~29% of FTSE 2016 dividends expected to be paid by energy or basic materials companies,
and the risk originating from the upcoming UK elections.
Figure 66: Expected upside on FTSE dividends climbed back to start
of year levels in H2-14 on the back of lower implied dividends and a
weaker British Pound relative to the US Dollar
Figure 67: Approximately 29% of FTSE dividends (ip for 2016) are
expected to be paid by Energy and Materials companies
Upside to JPM and IBES estimates for 2016 FTSE dividend futures
16%
Upside to JPM estimates
14%
Upside to IBES estimates
Utilities, 15.4
Industrials,
13.0
Consumer
Discretionary,
18.1
12%
Information
Technology,
1.0
Financials,
65.9
10%
Telecommunic
ation
Services, 15.8
8%
6%
Energy, 50.8
Materials,
26.4
4%
2%
Nov-14
Oct-14
Sep-14
Aug-14
Jul-14
Jun-14
May-14
Apr-14
Mar-14
Feb-14
Jan-14
0%
Health Care,
25.7
Consumer
Staples, 36.1
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15 December 2014
Marko Kolanovic
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Our Energy and Materials analysts believe that most FTSE 100 Energy and Basic Materials companies will likely do all
they can to maintain dividend payments, even as dividends are not covered by free cash flow/earnings at these commodity
prices levels. In other words, they do not expect outright cuts in DPS from these companies, but even a lack of growth
would be negative for the FTSE dividend futures.
Nikkei Dividends
Following a year of double-digit growth in Nikkei dividends, we expect the momentum to continue in 2015. With growth
initiatives remaining in place, we believe the government's priorities for corporate governance reforms will apply growing
pressure on cash-rich Japanese firms to enhance shareholder value. As a result, we think realized Nikkei dividends will
make new highs in index points and outperform Japan equities on a beta adjusted basis. 2015 and 2016 Nikkei dividends are
our favorite due to their close linkage to the corporate fundamentals and shareholder policies.
Corporate governance reforms should catalyze a strong dividend growth in Japan. With the completion of the
deleveraging process and cycle peak cash to asset ratios (Figure 68), Nikkei dividends turned up sharply and hit new records
in 2014 (in index points). Despite the strong dividend growth, the market-implied dividend payout ratios (dividend
price/consensus index earnings) are below 30% for 2015 and onward, less than the c.33% median payout ratio since 2001
(Figure 69). In 2015, we expect accelerated corporate governance reforms to provide additional incentives for companies to
boost the payout ratio. Further reform measures, such as the Companies Act Amendment (expected to go into effect in April
2015) and the introduction of the Corporate Governance Code (details expected in May/June 2015), should fuel changes in
the stance of Japanese companies regarding dividends.
The potential corporate tax rate cut is positive for earnings and dividends. In our view, the returning of a pro-growth
agenda increases the possibility of a corporate tax rate cut in 2015. While the implementation is not yet finalized, Abe’s
growth strategy promised to cut the tax rate from more than 35% currently to below 30% over the next few years. We think
a cut in corporate taxes will strongly complement the flow-through effects of the existing growth initiatives and provide
tailwind to Nikkei dividends if implemented at a quicker-than-expected pace.
Figure 68: Japanese companies have completed debt reduction and
are cash-rich
Figure 69: Nikkei market implied dividend payout ratio is below the
median payout ratio since 2001
Ratio
Ratio Ratio
Index Points
13%
90% 80%
300
12%
80%
70%
250
60%
11%
70%
50%
200
10%
60% 40%
150
9%
50% 30%
8%
40%
7%
30%
100
20%
10%
01
02
03
04
05
06
NKY Cash to Asset Ratio
Source: J.P. Morgan, Bloomberg
07
08
09
10
11
12
13
14
NKY Net Debt to Equity Ratio (R)
50
01 02 03 04 05 06 07 08 09 10 11 12 13 14 15 16
Historical NKY Div Payout Ratio
Market Implied Payout Ratio
Trailing 12M Div (R)
Source: J.P. Morgan, Bloomberg Note: Payout calculation excludes companies with negative
earnings
Support from a weaker Yen remains in place. Despite the emerging debate on the currency impact on corporate earnings,
the experience from 4Q14 to-date suggests that the Yen's depreciation against the dollar is associated with a 1 to 1 move in
Nikkei 225. Our FX strategy team expects the Yen to weaken toward 128 per dollar by the end of 2015. Based on the level
of 120 for Yen at the time of writing, this should introduce another c.6% upside to our top-down and bottom-up targets for
2017 dividends and onward, due to their high correlation with equities, but to a lesser degree for 2015 and 2016 dividends.
Fiscal year-end shifts introduce upside risks to 2015 dividends. The shift usually provides an extra dividend payment to
the current calendar year as companies bring forward the final dividend due in the next calendar year. We expect this trend
30
Marko Kolanovic
(1-212) 272-1438
15 December 2014
to accelerate as using calendar years likely improves efficiency in group management for companies with overseas
subsidiaries, and as more Japanese firms are encouraged to adopt International Financial Reporting Standards (IFRS) under
corporate governance reforms. This year, three cases of fiscal year-end shifts to December collectively contributed 2.6pts to
2014 Nikkei dividends while another two companies confirmed to do so from 2015. Along with an average of 2 pts per year
from memorial dividends (dividend in commemoration of company’s anniversary) since 2012, we estimate a combined
contribution of 6 index points due to one-off factors in 2015.
We continue to prefer using a top-down approach to forecast Nikkei dividend upside rather than solely relying on bottom-up
estimates. Our experience in recent years suggests analysts are conservative in reviewing their numbers during a structural
bull market. Hence we think top-down targets are more forward looking, while bottom-up estimates should provide a
valuation floor to the price of Nikkei dividends.
2015 and 2016 dividends offer the most attractive risk-reward characteristics: Incorporating the latest J.P. Morgan
economic forecasts for Japan, we revise up our top-down targets to 300 and 330 for 2015 and 2016 Nikkei dividends
respectively, with 6pts one-off factors in our 2015 targets. Admittedly, a potential higher payout ratio is not a direct input in
formulating our top-down outlook. However, we see upside risks in 2015 and 2016 dividends to our top-down targets if
there is a breakthrough in corporate governance reform. In balancing upside exposure with risk factors, we calculate the
ratio of the upside implied by our targets relative to the price volatility of Nikkei dividend across the curve. Our analysis
shows 2015 and 2016 dividends provide the highest return for every volatility point exposure. This affirms our view that
2015 and 2016 Nikkei dividends are best positioned to capture the structural trend of higher dividends in Japan.
For 2017 and beyond, we are rather cautious due to their high correlations to the Nikkei 225 index. While we believe 2017
and onward dividends have the potential to achieve levels of 341 points or more, we do not think the current price levels
represent an attractive entry point due to the risks of a short term reversal following the strong year end rally. We
recommend waiting for a better entry level for 2017 and longer maturities until there is more clarity on the impact of
stimulus on the economy or the occurrence of term structure flattening as a result of increased structured product flows.
Figure 70: We prefer positioning in 2015 and 2016 dividends
Nikkei 225 Dividend
Current price
Implied y/y growth
1Y correlation with NKY
Top-down forecast
Bottom-up forecast
Upside from current price
Top-down forecast
Bottom-up forecast
Ratio of upside to volaitlity
90D price volaitlity
Top-down forecast
Bottom-up forecast
52wk high
52wk high date
52wk low
52wk low date
2014
262.0
15.9%
2015
290.3
10.8%
60.6%
300.0
279.5
2016
315.5
8.7%
85.6%
330.0
307.8
2017
333.8
5.8%
92.4%
341.2
318.2
2018
345.5
3.5%
92.7%
352.8
329.0
2019
352.8
2.1%
93.0%
364.8
340.2
3.4%
-3.7%
4.6%
-2.5%
2.2%
-4.7%
2.1%
-4.8%
3.4%
-3.5%
5.2
0.6%
-0.7%
291.8
29-Jul-14
260.0
4-Feb-14
9.3
0.5%
-0.3%
318.8
7-Dec-14
279.8
15-Apr-14
11.5
0.2%
-0.4%
338.3
7-Dec-14
287.3
19-May-14
13.0
0.2%
-0.4%
350.0
8-Dec-14
291.3
19-May-14
14.4
0.2%
-0.2%
358.0
8-Dec-14
293.8
19-May-14
Source: J.P. Morgan, Bloomberg. Note: Targets for 2017 and onward are interpolated by the furthest GDP forecast for Japan, data as of December 10, 2014
H-shares and Hang Seng dividends
In Hong Kong, we prefer H-shares dividends over Hang Seng dividends going into 2015. Looking forward, our equity
strategists upgraded China to OW on expectation of further easing from the People’s Bank of China and growing interest
from domestic and international investors as a result of improved market access. On the other hand, Hong Kong is rated UW
due to its weaker economic momentum and linkage to US rates. With this macro outlook, we think H-shares dividends are
31
15 December 2014
Marko Kolanovic
(1-212) 272-1438
better positioned for the upcoming year for its higher earnings exposure to China. Besides, the improving Chinese equity
outlook should also fuel the performance of longer term H-shares dividends in our view.
Reliefs in China asset quality concerns add attraction to take more dividend risks. Based on GICS sector
classifications, Financials remain the dominant dividend payer in 2014, contributing 70% and 63% of total dividend index
points to H-shares and Hang Seng, respectively (Figure 71). Due to the high exposure to financials, in particular to the large
cap China banks, H-shares and Hang Seng dividends are vulnerable in times when fears of a China crisis intensify.
However, we think such concerns should be alleviated in the near term based on our banks analysts' view that easing asset
quality deterioration should far outweigh the NIM contraction impact. The reliefs in credit risks provide us comfort to
recommend taking more dividend risks by moving further out in the dividend curve to 2016 and beyond. However, in the
longer term, we concede progression on the structural reforms across fiscals, SOEs and capital markets in China would be
necessary to sustain any re-rating in H-shares and Hang Seng dividends.
Our preferred tenor is 2016 for both H-shares and Hang Seng dividends. Based on our bottom-up estimates, we see
attractive upside in both 2016 H-shares and Hang Seng dividends. The current flat term structure makes 2016 dividends
attractive to own as the market is anticipating very low single digit dividend growth, while our bottom-up estimates forecast
dividend growth to continue at a rate of 9.7% and 7.4% for H-shares and Hang Seng in 2016 respectively (Figure 72). While
term structure appears steeply inverted at the 2014-2015 juncture of Hang Seng dividend curve, we note it is attributed to a
special dividend paid out by Hutchison Whampoa (13 HK) and Cheung Kong Holdings (1 HK), which are unlikely to repeat
in the future. For longer term maturities, we believe there is more upside potential but liquidity can be of concern, especially
for Hang Seng dividends. Considering the balance of risk-reward and liquidity profile, our preferred dividend trade in Hong
Kong is 2016 H-shares dividends, given their 11% expected upside.
Figure 71: Financials remain the dominant dividend payer for H-shares Figure 72: Bottom-up estimates and marker prices for H-shares and
and Hang Seng in 2014
Hang Seng dividends
Contribution to total dividend index points by sector
Staples
Technology
HSCEI Divide nd
2014
2015
2016
2017
2018
Current price
435.4
461.0
464.1
466.0
473.0
5.9%
0.7%
0.4%
1.5%
470.7
516.3
561.3
610.1
8.1%
9.7%
8.7%
8.7%
2.1%
11.2%
20.4%
29.0%
2015
2016
2017
2018
Implied y/y growth
Healthcare
Bottom-up forecast
Utilities
435.4
Implied y/y growth
Telecom
Upside to target
Discretionary
Materials
Industrials
Energy
HSI Dividend
2014
Current price
908.5
Implied y/y growth
Financials
Bottom-up forecast
0%
10%
Source: J.P. Morgan, Bloomberg
20%
30%
HSCEI
40%
HSI
50%
60%
70%
80%
Implied y/y growth
Upside to target
908.5
851.5
848.6
846.3
843.2
-6.3%
-0.3%
-0.3%
-0.4%
848.4
911.4
962.4
1016.3
-6.6%
7.4%
5.6%
5.6%
-0.4%
7.4%
13.7%
20.5%
Source: J.P. Morgan, Bloomberg Note: HSCEI and HSI targets for 2017 and onward are
interpolated by the furthest GDP forecast for China and Hong Kong, data as of Dec 10, 2014
S&P 500 Dividends
S&P 500 dividends significantly underperformed the cash index in 2014, while exhibiting a subdued beta (Figure 73). In
our 2014 Outlook, we noted that long-dated S&P 500 dividends appeared overpriced and embedded excessively optimistic
growth forecasts. Our view largely played out over the past year, despite the lack of a meaningful market pull-back.
Long-dated dividends fell in absolute value this year (e.g. 2021-2023 contracts are down 7-8%), even though the S&P 500
rallied (up ~12% YTD) and 2014 realized dividends surprised to the upside (2014 realized dividends were ~2.5% higher
than implied at the start of the year). As a result of the underperformance of long-dated dividends, the S&P 500
dividend term structure has flattened significantly this year; however, the S&P 500 dividend curve remains upward
sloping and much steeper than the dividend curves on the Euro STOXX 50, FTSE 100, Hang Seng and H-Shares indices.
32
15 December 2014
Marko Kolanovic
(1-212) 272-1438
Figure 73: S&P 500 dividends underperformed this year, with a
muted beta to the cash index
65
60
2015
2017
2022
Figure 74: S&P 500 dividend payout ratio is near historical lows
100%
90%
2016
2019
80%
55
70%
50
60%
50%
45
40%
40
30%
35
30
Jan-12
20%
1871
Jul-12
Jan-13
Jul-13
Jan-14
Jul-14
1891
1911
1931
1951
1971
1991
2011
Source: J.P. Morgan, Shiller Data.
US corporate balance sheets remain healthy, which should support strong dividend growth next year. As shown in
Figure 75, Cash as % of Total Assets is near record high of 13.7%. S&P 500 companies are hoarding $4.1 trillion in cash
(of which $2.7 trillion is held by Financials) — to put this into perspective, there is enough cash held by non-Financials to
buy out 75% of the Russell 2000. Meanwhile, US corporates have not binged on cheap debt. As shown below, S&P 500
debt as % of total assets is at a trough level of 23%. This decline is mainly driven by Financials deleveraging after the last
recession, but excluding financials declined slightly to 28% of total assets. Furthermore, debt outstanding is at multi-decade
lows as a % of market capitalization, and payout ratios are near historical lows (Figure 74). The high cash and low debt
levels are supportive of robust dividend growth in 2015.
Figure 75: Cash levels are near record high at 13.7% of total assets...
14.1%
14%
13.7%
11.8%
12%
11.2%
10%
8%
8.0%
4%
1996
1999
Source: J.P. Morgan, Factset.
2002
2005
2008
2011
35%
30%
S&P 500
S&P 500 (ex-Financials)
6%
Figure 76: ...while debt levels are low, suggesting along with low
interest rates and credit spreads, that US corporates face a low debt
service burden
40%
37%
36%
2014
28%
25%
20%
1996
S&P 500
S&P 500 (ex-Financials)
1999
2002
2005
2008
23%
2011
2014
Source: J.P. Morgan, Factset.
We are positive on the 2015 and 2016 dividend swaps, as they offer decent upside to bottom-up expectations and limited
risk as they get pulled to realized. 2015 dividend swaps currently price in ~6% YoY growth ̵ around half the growth rate
dividends recorded this year. Given the healthy US corporate balance sheets discussed above and our Equity Strategists’
expectation that 2015 earnings will grow at a robust 8% pace, we believe the 6% implied growth is easily achievable.
Bloomberg bottom-up estimates call for ~10% growth next year (a reasonable target, in our view), giving ~4% expected
upside on this contract. Additionally, given the strong corporate cash balances, our economists’ expectation that US growth
is likely to continue its strong pace heading into 2015, and the short time period until these dividend swaps realize,
downside risk is limited in our view.
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15 December 2014
Marko Kolanovic
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Similarly, 2016 dividends offer an attractive risk reward in our view, as they trade at a ~8% discount to bottom-up estimates
(43.5 implied vs. 47.1 points expected according to Bloomberg forecasts) and should get pulled to realized over the course
of next year.
We note the Energy sector presents risk to the 2015/16 dividends, due to the recent fall in Oil prices. Energy companies are
expected to deliver ~12% of total S&P 500 dividends in the next two calendar years, and account for ~25% of dividend
growth. Additionally, this sector’s dividends are relatively concentrated, with 2 names (Exxon and Chevron) accounting for
close to half of the sector total. Continued weakness in Oil prices could reduce these companies’ willingness to grow their
dividends, presenting some downside risk to their forecast dividend growth. That said, risks appear manageable as JPM
Integrated Oils analyst Phil Gresh notes Exxon appears well equipped to weather a downturn in oil and has no need to cut
capital plans due to their strong FCF generation, while Chevron has reiterated its commitment to growing its dividend and is
much more likely to cut buybacks than dividends9.
We hold a neutral view on long-dated S&P 500 dividends. As the dividend curve flattened, the long-end of the curve
now prices in ~4% annualized long-term growth, compared with ~6% priced in a year ago. As we noted last year, the
historical average increase in dividends in non-recession years was ~7%, suggesting that long-dated contracts are now
pricing in a non-trivial risk of a recession at some point before expiry. We view risks on long dated dividends as relatively
balanced - these contracts could experience some mark-to-market gains if the market continues to rally and/or if there's a
significant wave of new long-dated put hedging demand (which causes market makers to buy dividends as a hedge);
however, these long-dated contracts are likely to suffer losses at some point before expiry when the market next experiences
a meaningful sell-off and/or the US enters the next recession.
Ratio to front year dividend swap
Figure 77: The S&P 500 dividend curve flattened significantly this
year as long-dated dividend swaps underperformed
180%
170%
160%
150%
140%
130%
120%
110%
100%
90%
31-Dec-13
10-Dec-14
0
2
4
6
Years to Expiry
9
8
10
Figure 78: S&P 500 realized (blue) and implied (grey) annual dividend
growth rates
25%
20%
15%
10%
5%
0%
-5%
-10%
-15%
-20%
-25%
1994 1998 2002 2006 2010 2014 2018 2022
See Exxon Mobil Corp - Good Defense in a Downside Scenario, and Chevron Corp - Cash Conservation Levers Likely Pulled Soon
34
15 December 2014
Marko Kolanovic
(1-212) 272-1438
Delta 1 Funding
Funding costs are an important consideration for derivatives investors; they determine the cost of carrying unfunded delta-1
exposure (e.g. through equity index futures or swaps), and factor into the pricing of equity options by impacting the forward
price. For example, the increase in funding spreads in the last ~2 years has led collateralized futures to underperform their
cash total return indices (as we discuss toward the end of this section), which has important implications for passive
indexers who use these instruments for cash equitization.
In 2014, implied funding spreads for equity delta 1 instruments declined YoY across most developed market indices (Figure
79), as banks adjusted their delta 1 business model to cope with the new reality (see gray box below). For example, this
trend can be seen from the average roll costs for S&P 500 Emini futures, which have been trending lower since March 2013,
outside of December (year-end) roll periods (Figure 80). However, similar to 2013, global implied funding spreads rose
sharply into year-end (particularly short-dated tenors), due to the balance sheet and funding constraints which most delta 1
desks face around the end of the year.
Figure 79: Short-dated implied funding spreads have normalized
throughout the year, but experienced a strong richening into yearend similar to 2012 and 2013
3M implied funding rates
Figure 80: S&P 500 Emini futures roll costs have similarly been
trending lower (outside of December rolls)
VWAP roll cost vs. LIBOR FV (bps)
60
+52bps
0.8%
50
0.4%
+42bps
40 +35bps
0.0%
+33bps
30
-0.4%
+46bps
+33bps
+24bps
+23bps
20
-0.8%
SPX
NKY
SX5E
FTSE
SMI
Sep-14
May-14
Jan-14
Sep-13
May-13
Jan-13
Sep-12
May-12
Jan-12
-1.2%
10
0
Dec-12 Mar-13 Jun-13 Sep-13 Dec-13 Mar-14 Jun-14 Sep-14
The new regime for funding spreads and how banks are responding
The Equity Delta 1 business utilizes balance sheet resources, which are needed to fund the traded assets. The
introduction of new regulations such as the LCR (Liquidity Coverage Ratio), the Net Stable Funding Ratio (NSFR) and
the Leverage ratio, is overall forcing banks to hold more and better quality collateral against RWA (Risk Weighted
Assets). Overall this has led to an increase in the cost of funding assets for Delta 1 equity trading desks, while Leverage
ratio regulations will increase focus on containing overall RWA notional. This increase in funding is not homogeneous,
but depends on the type of instrument and on the actual underlier being funded, which in turn led to a much greater
emphasis on collateral management. As banks have progressively adjusted their businesses to the new rules and pricing
environment, implied funding spreads declined.
The picture is different when looking at long-dated funding spreads (Figure 81), which for some indices remain close to the
widest levels on record. For example, in Europe, the long-dated part of the borrow curve is strongly influenced by structured
product flows, as issuing structured products leaves banks with the need to hedge short forward positions given that most
client trades are overall net long delta. The reasonably robust issuance of structured products in Europe, in conjunction with
long dated call buying from institutional investors, contributed to the strong demand for long-term Euro STOXX 50
funding, which has in tern kept the spread levels close to their widest historically. On the other hand, on the Nikkei 225,
long-dated funding rates trended lower due to the slowdown in structured product issuance, while short-dated funding rates
have risen recently going into year-end, in line with what we observe on the S&P 500 and Euro STOXX 50 (Figure 82).
35
15 December 2014
Marko Kolanovic
(1-212) 272-1438
Figure 81: Long-dated funding spreads remained close to historical
highs for some indices, particularly the Euro STOXX 50
Figure 82: Nikkei 225 implied funding rates
Implied Funding Rate (%)
5Y implied funding rates
1.2%
0.8%
0.4%
0.0%
-0.4%
SMI
May-14
May-13
FTSE
May-12
May-11
SX5E
May-10
NKY
May-09
May-07
May-06
May-08
SPX
-0.8%
Going forward, we expect a continued decline in short-dated funding spreads (though at a slowing pace), but we do not
expect a reversion to the levels recorded before the start of the new regime. This normalization will not likely affect funding
spreads at year end, and the strong seasonality we experience in December will likely remain similar in size and
characteristics to what we experienced since December 2012. Long-dated implied borrow levels might decline to an extent,
but will remain elevated due to continued structured product issuance, especially for the Euro STOXX 50. The high positive
carry that can be earned by trading long-dated vs. short-dated funding will likely attract client interest, but we do not expect
that clients will be able to completely offset the diminished ability by delta 1 desks to supply long-dated funding. We
continue to find Euro STOXX 50 borrow monetization trades attractive due to the attractive carry and favorable funding
curve slide (see the Trade Ideas section).
Analyzing TR cash tracking vs. futures
The increased delta 1 funding spreads are leading a growing number of investors to reassess their approach to passively
tracking equities. The charts below show the comparative performance of futures collateralized by a local currency cash
account earning LIBOR relative to a gross TR investment in stocks10.
Based on the assumption of earning LIBOR flat, we find that for most indices the collateralized futures replication
underperformed the cash TR replication over the last 2 years, after tracking almost perfectly in the previous years (Figure 83
and Figure 84). The two main factors that can lead to the performance differential between collateralized futures and cash
are dividends and implied funding, but the impact of funding has been dominant in the recent years relative to dividends.
10
Other assumptions are: futures commission of 1bp per roll, quarterly rolls executed 5 days prior to expiry, cash commission of 3bp per
annum and gross dividends for all indices ex FTSE 100.
36
Marko Kolanovic
(1-212) 272-1438
15 December 2014
Figure 83: Relative performance of collateralized futures vs. gross
TR cash – Developed Market indices
Figure 84: Relative performance of collateralized futures vs. gross
TR cash – Asian indices
Performance difference of Gross TR cash vs. collateralized futures
(all series rebased to 100 on Jan-07)
Performance difference of Gross TR cash vs. collateralized futures
(all series rebased to 100 on Jan-07)
4
2
2
0
0
-2
-4
-2
-4
-6
S&P 500
FTSE 100
Euro STOXX 50
-8
-10
Jan-07 Jan-08 Jan-09 Jan-10 Jan-11 Jan-12 Jan-13 Jan-14
-6
-8
Hang Seng
TOPIX
Nikkei
-10
-12
-14
Jan-07 Jan-08 Jan-09 Jan-10 Jan-11 Jan-12 Jan-13 Jan-14
So what can investors do to optimize their investment in the new higher funding environment? Moving to fully funded
investments (e.g. ETFs or equity cash replication) is an option, but not all investors are able/willing to make this change.
The problem in our view is better approached from a different angle - i.e. what investors can do to either improve the delta 1
funding they face, or to take advantage of the higher funding. In its simplest form, the latter involves buying the
expensive-to-fund assets and swapping back their performance to a counterparty, thus receiving a high funding spread. This
is particularly beneficial around year-end, when constraints on balance sheets make funding some assets particularly
expensive. As an illustration, a 3M funding trade on European blue chip names at the time of writing would be priced in the
markets at approximately Euribor 3M +35 bps, and funding spreads for other assets can be even higher.
Another solution is to optimize the use of collateral, using excess cash to fund assets that are particularly expensive to carry
in the market. For example, one can buy swaps/futures on cheaper to finance portions of the portfolio that are currently held
in physical equities, and use the excess cash derived from this shift to fund the purchase of equities that are more expensive
to finance. As an illustration, in the US Russell 2000 futures trade persistently cheap due to the high borrow cost on small
cap stocks and generally weaker positioning in these futures (e.g. they are often shorted by small cap managers as a beta
hedge against their alpha-generating small cap portfolio). An investor with a multi-cap US portfolio could carry small cap
stocks via futures or swaps, and use the freed up cash to buy large cap equities that are relatively more expensive to finance
(rather than holding large cap stocks synthetically).
37
15 December 2014
Marko Kolanovic
(1-212) 272-1438
Derivatives Trades for 2015
Macro/Directional Trades
Eurozone upside trades
JPM Economist David Mackie expects economic growth in the Euro area will step up significantly next year, and his
forecast of an annualized growth pace of 2% is well above market consensus. A good part of the growth uptick will be
imported, as the negative impact on the region due to weak global economic growth is expected to become positive in 2015,
mostly driven by growth in the US and by the favorable effect of lower oil prices. Another key positive driver will be the
expansion of the ECB balance sheet, which our European economists think will begin in earnest in January with the
announcement of Sovereign QE (now their base case), of the purchase of non-financials corporate bonds and of several
improvements to the current TLTRO terms. Further positive drivers for Euro zone equities are the impact of a lower Euro,
the reduced expected fiscal tightening in some of the Peripheral countries and in France, and the overall bottoming-out of
credit conditions.
Figure 85: Despite their uptick in H2-14 Euro zone index volatilities
remain relatively low in historical terms
1Y ATM implied volatilities
1Y 100120% Skew
IBEX
Jan-14
Jul-13
Jan-13
Jul-12
Jan-12
FTSEMIB
SX7E
Jul-14
Euro STOXX 50
55%
50%
45%
40%
35%
30%
25%
20%
15%
10%
Figure 86: Euro-zone equity indices skews are flat relative to their
histories and relative to most other DM indices
Current
5Y
%ile
Avg
Max
Min
1Y chg
SX7E
1.4%
1%
3.4%
6.1%
1.3%
-0.5%
FTSEMIB
1.8%
5%
3.5%
6.0%
1.6%
-0.5%
IBEX
2.3%
5%
3.9%
6.1%
2.0%
-0.1%
SX5E
2.5%
12%
3.7%
6.0%
1.9%
0.1%
EEM
2.6%
4%
3.8%
5.9%
2.1%
-0.6%
DAX
3.0%
6%
4.0%
6.1%
2.7%
0.1%
SMI
3.0%
62%
2.8%
4.5%
1.5%
1.4%
UKX
3.5%
41%
3.8%
5.9%
1.4%
1.5%
SPX
4.2%
39%
4.7%
6.4%
2.6%
0.7%
Despite a limited pickup during H2-14, Eurozone index implied volatilities remain relatively low in historical terms (Figure
85), while Eurozone equity index skews are close to record levels of flatness (Figure 86). This leads us to generally find
Dec-15 call spreads attractive.
Long Euro STOXX 50 call spreads. These price well due to the flat upside skew of the Euro STOXX 50 index and entry
levels look attractive as we expect a pick up in implied vols next year. For example, a Euro STOXX 50 Dec-15 3400-3800
call spread costs indicatively 2.6% of notional, offering a 26% discount to an outright 3400 call and a 1 to 4.8 cost-to-max
payout ratio (spot ref. 3159.11).
Long IBEX call spreads. IBEX has one of the flattest call skews in Europe and also a higher implied vol than many other
European indices. This makes the IBEX a particularly good candidate for call spreads in our view. Indeed, a Dec-15
105%/120% call spread has a 1 to 4.2 cost to payout ratio and costs 3.57% indicatively vs. 4.71% for an outright 105% call
(IBEX spot ref. 10461.60). Furthermore, peripheral Eurozone is looking cheap on many valuation metrics with meaningful
earnings upside potential. Spanish growth expectations in particular have picked up over the year with Spanish PMIs
pointing to double digit EPS growth. Our equity strategists prefer Spain over Italy and highlight that Spain has made more
progress on the fiscal front compared to Italy and has a much stronger activity momentum. However, JPM quant equity
analyst Khuram Chaudhry thinks that Spain’s EPS trend has peaked following the largest drop in earnings revisions among
European countries in November and political risks remain, in our view.
38
Marko Kolanovic
(1-212) 272-1438
15 December 2014
Long swaps or call options on the JPM Eurozone Recovery Basket. One of the themes that are expected to perform well
in 2015 according to EMEA equity strategist Mislav Matejka is that of stocks exposed to a Eurozone domestic recovery (see
Equity Strategy: Year Ahead 2015 for more details). These stocks are expected to benefit in our central scenario for the
region and are cheap on a P/E relative basis to the rest of the Eurozone according to our strategy team, having de-rated in
relative terms throughout 2014.
The J.P. Morgan Eurozone Recovery Basket (JPDEER15 <index> on Bloomberg) is comprised of Eurozone stocks with
significant domestic exposure (>30%) and that are most positively correlated to Euro area PMIs. The basket can be bought
via TRS at indicatively 3M LIBOR + 38bps. Alternatively a 1Y ATM call option on the basket costs 7.45%, and it is
possible to buy 1.3x 1Y ATM calls and sell 1Y ATM put for zero cost, indicatively (Table 16).
Table 8: J.P. Morgan ’15 Eurozone recovery basket – JPDEER15 <Index>
Ticker
CABK SM
G IM
ATL IM
MS IM
AGS BB
INGA NA
GLE FP
DG FP
ENEL IM
AC FP
HMB SS
SEV FP
UCG IM
CA FP
RAND NA
RNO FP
TIT IM
ALV GR
MEO GR
SGO FP
EZJ LN
UG FP
CAP FP
PRY IM
DPW GR
REP SM
ADEN VX
BOSS GR
TKA GR
AGL IM
TOD IM
SIE GR
AGN NA
IFX GR
LR FP
HEI GR
Sector
FINANCIALS
FINANCIALS
INDUSTRIALS
DISCRETIONARY
FINANCIALS
FINANCIALS
FINANCIALS
INDUSTRIALS
UTILITIES
DISCRETIONARY
DISCRETIONARY
UTILITIES
FINANCIALS
STAPLES
INDUSTRIALS
DISCRETIONARY
TELECOMS
FINANCIALS
STAPLES
INDUSTRIALS
INDUSTRIALS
DISCRETIONARY
IT
INDUSTRIALS
INDUSTRIALS
ENERGY
INDUSTRIALS
DISCRETIONARY
MATERIALS
DISCRETIONARY
DISCRETIONARY
INDUSTRIALS
FINANCIALS
IT
INDUSTRIALS
MATERIALS
Country
SPAIN
ITALY
ITALY
ITALY
BELGIUM
NETHERLANDS
FRANCE
FRANCE
ITALY
FRANCE
SWEDEN
FRANCE
ITALY
FRANCE
NETHERLANDS
FRANCE
ITALY
GERMANY
GERMANY
FRANCE
BRITAIN
FRANCE
FRANCE
ITALY
GERMANY
SPAIN
SWITZERLAND
GERMANY
GERMANY
ITALY
ITALY
GERMANY
NETHERLANDS
GERMANY
FRANCE
GERMANY
W. European Exposure
100%
100%
100%
100%
95%
93%
84%
82%
82%
76%
72%
71%
70%
69%
69%
69%
69%
69%
69%
67%
66%
66%
66%
63%
63%
63%
62%
60%
59%
57%
55%
53%
50%
41%
35%
30%
Basket Weight
2.8%
2.8%
2.8%
2.8%
2.8%
2.8%
2.8%
2.8%
2.8%
2.8%
2.8%
2.8%
2.8%
2.8%
2.8%
2.8%
2.8%
2.8%
2.8%
2.8%
2.8%
2.8%
2.8%
2.8%
2.8%
2.8%
2.8%
2.8%
2.8%
2.8%
2.8%
2.8%
2.8%
2.8%
2.8%
2.8%
39
Marko Kolanovic
(1-212) 272-1438
15 December 2014
Japan: Thematic trade ideas for the 3rd year of Abenomics
We believe 2015 will prove to be another great year for Japanese equities. The reinforcement of a pro-growth policy
leadership, as evidenced by the fresh stimulus from BoJ and confirmed support from GPIF, has catalyzed a QE-fuelled rally
to form in Japan. Together with strong corporate earnings and progression in structural reforms, our Japan equity strategists
forecast a peak cycle level of 24,000 for Nikkei 225 by early 2017.
We prefer call spreads and ratios on Nikkei 225 for upside exposure. With one of the highest absolute implied volatility
levels and one of the flattest upside skews, we prefer using call spreads and ratios on Nikkei 225 to extract upside volatility
richness while positioning for further upside (Figure 87Figure 27). Furthermore, we prefer owning 1Y over shorter dated
call spreads due to our outlook of reduced policy uncertainties into 2015. In our market commentary (Figure 27), we
attribute the inversion of the term structure during 1H14 to the singular focus on easing from the Bank of Japan amid
volatility injected by the consumption tax hike. As Japan policy makers reaffirmed their support by providing monetary
stimulus and postponing the 2nd consumption tax hike, we expect that reduced policy uncertainties will work to normalize
the currently inverted volatility term structure by applying pressure on the short end. For longer dated volatility, we expect
support from structured product hedging activities as issuers will need to reduce their short vega positions when markets
move higher. Therefore we recommend 1Y call spreads to position for further upside or using call ratios if a slightly
negative vega is desired.
Buy Nikkei 225 1Y 110%-125% call spread costs 2.95% (41% savings to 110% call, 5.1X max payout)
Buy Nikkei 225 1Y 110%-125% 1X2 call ratio on Nikkei 225 costs 0.95%
Figure 87: The 110% and 125% volatility spread of Nikkei 225 is low
compared to its global peers and own history
Volatility spread
Figure 88: Correlation between spot and volatility moves remained
largely positive for Nikkei 225
Index Correlation
40%
5.0%
30%
4.0%
20%
3.0%
10%
2.0%
0%
-10%
1.0%
-20%
0.0%
-30%
-1.0%
-40%
-2.0%
Dec-09
-50%
Dec-10
HSCEI
Dec-11
NKY
Dec-12
SPX
Dec-13
Dec-14
SX5E
-60%
Dec-11
NKY 12M correlation between 12 ATM vol moves
(ex-skew) and spot moves
Jun-12
Dec-12
Jun-13
Dec-13
Jun-14
Dec-14
Investors can also consider ‘appearing’ call spreads and knock-out calls. For the appearing call spread, client buys 1Y
110% call and sells 1Y 125% call that knocks in at a 130% barrier (continuously monitored). For a small extra premium to
the vanilla call spread, the appearing call spread offers an identical payout to a 1Y 110% call if the knock in event does not
occur. For a 1Y 110% call with a 125% knock out barrier, the cost is much cheaper to the corresponding call spread, as the
option will cease to exist when the price of the underlying breaches the knock-out barrier.
Buy NKY 1Y 110%-125% call spread with the 125% call KI at 130% costs 3.10% (vanilla call spread 2.95%)
Buy NKY 1Y 110% call with 125% continuous KO costs 0.55%
Sell put spreads to finance upside structures. The unprecedented policy actions from Bank of Japan have raised
conviction that the bull market will be enduring among many investors. In that case, selling put spreads benefits from the
flat downside skew and appears appealing as a source to finance upside structures. We prefer selling put spreads over puts
as the loss is limited to the lower put strike.
Sell NKY 1Y 90%-77% put spread and buy 1Y 110%-125% call spread for zero cost
40
Marko Kolanovic
(1-212) 272-1438
15 December 2014
In addition to pure equity options, investors can consider hybrid structures to hedge equity risks with reduced costs. Even
though not at the highest levels, the current correlation level between Nikkei 225 and USDJPY remains elevated in its
history and the implied level (c.60%) looks reasonable to sell (Figure 89). From a long term perspective, the correlation
between Japan equities and currency has not always been strong. The current high levels of equity and currency correlation,
which were only evident during the years of global financial crisis and the start of Abenomics, seem abnormal in a historical
context. Looking forward, we think a further market rally led by sectors sensitive to domestic growth as well as migration of
production bases overseas by Japanese manufacturers could act to drive the correlation lower.
Besides the equity and currency relationship, structures based on Japan 10Y swap rates and Nikkei 225 are worth
highlighting. We think the equity-rates correlation would remain under downward pressure as Bank of Japan's
unprecedented stimulus is set to keep equity buoyant and rates low.
Our base case for Japan is higher equity, weaker yen and lower swap rates, but we concede there are risks to our outlook
given both domestic and global macro uncertainty. Below, we show a few hybrid structures that provide attractive discount
to vanilla options to assist investor hedging both upside and downside risks.
Equity-currency hybrid structures (implied correlation 60%)
Nikkei 1Y 110% calls contingent on USD/JPY below 130 at expiry costs 2.70% (47% savings to vanilla calls)
Nikkei 1Y 90% puts contingent on USD/JPY above 110 at expiry costs 3.10% (40% savings to vanilla puts)
Equity-rates hybrid structures (implied correlation 25%)
Nikkei 1Y 110% calls contingent on JYSW10 below 0.65% at expiry costs 2.55% (49% savings to vanilla calls)
Nikkei 1Y 90% puts contingent on JYSW10 above 0.75% at expiry costs 1.85% (64% savings to vanilla puts)
Figure 89: NKY and USDJPY 1Y weekly correlation history
Figure 90: NKY and Japan 10Y swap rates 1Y weekly correlation
history
%
%
80%
60%
60%
50%
40%
40%
30%
20%
20%
0%
10%
0%
-20%
-40%
Dec-94
-10%
Dec-98
Dec-02
Dec-06
Dec-10
NKY-USDJPY 1Y Weekly Correlation
Dec-14
-20%
Dec-94
Dec-98
Dec-02
Dec-06
Dec-10
NKY-JYSW10 1Y Weekly Correlation
Dec-14
Call spreads on sectors that benefit from inflation. Besides the index trade ideas, we believe sectors that are leveraged to
domestic demand and an improving business cycle are set to outperform. Specifically, our strategists recommend
overweight exposure to banks, real estate, non-bank financials, and trading houses, followed by autos and tires. Among
TOPIX sectors with liquid options market, we prefer call spreads on Banks (TPNBNK), Real Estate (TPREAL) and
Transportation Equipment (TPTRAN) as candidates to capitalize on the ongoing pivot from deflation to inflation.
Buy TPNBNK 1Y 110%-125% call spread costs 3.6% (43% savings to 1Y 110% call)
Buy TPREAL 1Y 110%-125% call spread costs 4.0% (50% savings to 1Y 110% call)
Buy TPTRAN 1Y 110%-125% call spread costs 3.3% (43% savings to 1Y 110% call)
41
Marko Kolanovic
(1-212) 272-1438
15 December 2014
China: Index and sector options to trade policy catalysts and market euphoria
China is one of our top OW markets within the Asia Pacific equity portfolio. As for China, our bull case is supported by
potential easing measures, including two RRR cuts in 2015 according to J.P. Morgan’s China economists, as well as
increased interest from domestic and international investors on A-shares due to improved market access. Additionally, our
economists expect the Chinese government to continue fiscal, financial and state owned enterprise (SoE) reforms, which
should support the performance of financials and SoE reform beneficiaries.
Market euphoria is set to cause volatility. While easing policies and the launch of Shanghai-Hong Kong Stock Connect
both propelled the Chinese stock market, the 40%+ gains in CSI 300 from the lows in July to the level at the beginning of
December 2014 was reminiscent to the 2006-2007 ramp-up, a period that features frenzy buying from retail investors.
Behind the recent stock market boom, we started to see signs that domestic retail investors are turning back to the equity
market. After years of disappointing performance, both new stock account opening and the percentage of active trading
accounts are approaching their 5-year peaks (Figure 91). Besides, leverage has contributed to the recent market momentum
following fewer restrictions on local brokerages in recent years. The total margin trading balance more than doubled from
July 2014 levels (when market started to rise), and measures 6.8% of free-float market cap currently (Figure 92).
With our bullish view on China equities, the growing momentum of China onshore equities is of particular note when
devising trading strategies. Given A-shares are broadly trading at a more than 10% premium to their H-shares counterparts
at the time of writing; we note the risks of H-shares to catch up fiercely to close the A-H price differentials. To position for
the next China rally at a time when upside skews remain flat, we see risks of using call ratios in case China share
performance explodes on the way up, and prefer call spreads and call flies for upside exposure.
Figure 91: Both new and active A-shares brokerage accounts are
approaching their 5-year highs.
%
Figure 92: Onshore margin trading balance hits 6.8% free float market
cap of China A-shares (SHSE +SZSE)
Thousand %
25%
20%
15%
600
500
400
300
10%
5%
200
100
0%
0
Dec-09
Dec-10
Dec-11
Dec-12
Dec-13
Dec-14
A-shares % Active Accounts
New A-shares Accounts (R)
Source: J.P. Morgan Equity Derivatives Strategy, CSDC
Index
8%
4,000
7%
3,500
6%
5%
3,000
4%
2,500
3%
2%
2,000
1%
0%
1,500
Apr-10
Apr-11
Apr-12
Apr-13
Apr-14
Margin Trading Balance / Free Float Market Cap (SHSE+SZSE)
CSI 300 (R)
Source: SHSE, SZSE, J.P. Morgan Equity Derivatives Strategy, Bloomberg
We prefer call spreads and call flies and on H-shares for China upside exposure. Similar to Nikkei 225, implied
volatility of H-shares is expensive compared to its global peers while its upside skew is strongly inverted. In addition to
buying call spreads, we like using call flies, which are also priced favorably due to the inverted upside skews. The call fly
can be decomposed into a long call ratio (buying one near ATM call and sell two middle OTM calls) and a long far OTM
call position. With a small extra premium, the addition of a far OTM call reduces the risks of a long call ratio position
should the next stage of the rally go beyond expectations and result in a loss on the call ratio.
Catalysts for next year include National People’s Congress in March, MSCI review of China A-shares market status in June
and further easing (our economists expect 1 rate cut in 1Q15 and two RRR cuts in 1Q15 and 2Q15). Considering
momentum in China equities and an eventful 1H15 macro calendar, we recommend Jun-15 call flies and call spreads for
their balanced trade off between costs and risks for China upside exposure. Our preferred index is H-shares (HSCEI) as Ashare are broadly trading at more than 10% premium to H-shares but investors can consider options on FTSE China A50
(XIN9I) for pure A-share exposure. Barrier options can be considered for investors seeking higher cost savings.
42
15 December 2014
Marko Kolanovic
(1-212) 272-1438
Table 9: Indicative options pricing of on H-shares and FTSE China A50
H-Shares (HSCEI)
FTSE China A50 (XIN9I)
6M 105%-120% call spread (offer)
2.97%
3.95%
6M 105%-120%-135% 1X2X1 call fly (offer)
2.05%
2.55%
6M 105% call with 120% continuous KO (offer)
0.75%
0.67%
6M 105%-120% call spread with the 120% call KI at 130% (offer)
3.08%
4.18%
Source: J.P. Morgan Equity Derivatives Strategy. Note: Barriers are continuously monitored.
Buy China Banks basket and SOE reform beneficiaries on policy focused investing. Given the role of policy outlook on
Chinese equities, we believe there are opportunities on the policy related themes. If two RRR cuts realize in 2015, in line
with our China economist’s forecast, it should alleviate the asset quality concerns and deep valuation discount in China
banks. Investors can use the J.P. Morgan China Bank Basket <JPHCHBK2> to hedge against this upside risk in China
banks. Another theme to focus in the long term is SOE reform. State-owned enterprises (SOEs) play a dominant role in the
China economy, representing 60% of the Shanghai Stock Exchange and MSCI China universe free floats. Their reform is a
key area of focus under the 18th Third Party Plenum with the goals to break monopolies and introduce competition.
Investors can gain exposure to this theme via J.P. Morgan China SOE Reform Beneficiaries <JPHCHSOE>.
Figure 93: Relative performance of China thematic baskets (past 1Y)
130
JPHCHBK2
JPHCHSOE
MXCN
120
110
100
90
80
70
Dec-13
Apr-14
Aug-14
Dec-14
Figure 95: China SOE Reform Beneficiaries <JPHCHSOE>
composition
Ticker
Name
6881 HK
6837 HK
6030 HK
3898 HK
1186 HK
1099 HK
1766 HK
728 HK
3323 HK
941 HK
914 HK
371 HK
386 HK
762 HK
857 HK
392 HK
Cgs-H
Haitong Securi-H
Citic Securiti-H
Zhuzhou Csr-H
China Rail Cn-H
Sinopharm-H
Csr Corp Ltd-H
China Telecom-H
China Natl Bdg-H
China Mobile
Anhui Conch-H
Bj Ent Water
Sinopec Corp-H
China Unicom Hon
Petrochina Co-H
Beijing Enterpri
Curr
Price
11.02
22.25
31.75
33.35
9.44
28.05
7.89
4.68
7.55
93.85
27.35
4.69
6.5
11.02
8.52
59.25
Figure 94: China Bank Basket <JPHCHBK2> composition
Ticker
Name
Curr
Mkt Cap Avg T/O Index
Price
($mn)
($mn) Wgt (% )
1988 HK China Minsheng-H
9.61
8,596
66.4
18.6
998 HK
China Citic Bk-H
6.07
11,654
38.8
15.9
3988 HK Bank Of China-H
4.32
46,603
218.0
13.1
1288 HK Agricultural-H
3.89
15,428
62.7
11.2
1398 HK Icbc-H
5.68
63,603
224.5
10.9
939 HK
Ccb-H
6.41 198,825
203.5
10.3
3968 HK China Merch Bk-H
17.5
10,365
60.5
10.1
3328 HK Bank Of Commun-H
7.12
32,162
37.1
9.9
Source: J.P. Morgan, Bloomberg. * The J.P. Morgan China Bank Basket <JPHCHBK2> is
composed of 8 China Banks listed on the HKSE, and was established with equal weights as of
27-Sep-2010. Based on 1/3 of 3M ADV of constituent stocks, the basket trades USD 81 mn/day.
Figure 96: Indicative pricing of bullish strategies for JPHCHSOE and
JPHCHBK2.
Mkt Cap Avg T/O
Index
($mn)
($mn) Wgt (% )
6M 105% call (offer)
2,404
50.0
10.2
4,285
60.9
9.6
Implied volatility
4,827
49.0
9.1
2,355
8.9
6.7 6M 105%-120% call spread (offer)
2,529
21.5
6.6
Savings vs outright call
4,317
20.6
6.5
2,060
9.5
6.1 Source: J.P. Morgan, Bloomberg
8,379
37.4
6.0
2,805
19.5
5.5
246,945
220.5
5.4
4,586
45.9
5.2
5,269
8.0
4.9
21,396
109.1
4.8
34,011
61.6
4.5
23,192
113.5
4.5
9,818
12.6
4.4
JPHCHBK2
JPHCHSOE
5.45%
5.10%
28.0%
26.0%
3.45%
3.40%
36.7%
33.3%
Source: J.P. Morgan, Bloomberg. * The J.P. Morgan China SOE Reform Basket <JPHCHSOE>
is composed of 15 stocks identified by our analysts that are likely to be positively impacted by the
SOE reform in China (see “China strategy: Impact of SOE reform on sectors”, Adrian Mowat,
18-Aug-14).The basket was established with equal weightings as of August 18, 2014. Assuming
1/3 of the 3-month average daily turnover of constituent stocks, the basket trades USD 45mn/day
43
Marko Kolanovic
(1-212) 272-1438
15 December 2014
China / Hong Kong relative value via outperformance options
While the outlook of Chinese equities is lifted by the potential monetary stimulus and the return of local investors, Hong
Kong equities face the headwinds of higher US rates and weaker economic momentum, according to our equity strategists.
As a result, our equity strategist recently upgraded China to OW and maintained an UW rating on Hong Kong.
To implement the China (OW) versus Hong Kong (UW) outperformance view via options, call switch or outperformance
option strategies can be used on H-shares (HSCEI) vs. Hang Seng (HSI). For the call switch strategy, investors are going
long HSCEI call options while going short call options on HSI to implement the relative value trade on the upside only.
Indicatively, a 6M ATM call switch on HSCEI versus HSI costs a net premium of 2.2%.
Outperformance options provide a payoff based on the relative performance between two assets, minus the strike. Unlike
call switches, outperformance options provide the relative performance exposure on the upside and downside. While the
option premium is higher, losses are limited to the premium paid. The pricing also works nicely with highly correlated pairs
such as HSCEI and HSI, which has a 1Y realized correlation of 89% based on daily returns. Indicatively, the 6M ATM
outperformance option on HSCEI versus HSI can be purchased at 4.4% premium.
Figure 97: Rolling backtest of 6M ATM HSCEI vs. HSI call switch over Figure 98: Rolling backtest of 6M ATM outperformance option on
past five years.
HSCEI vs. HSI over past five years.
%
Thousand %
10%
Long 6M HSCEI ATM Call versus Short 6M HSI ATM Call
9%
6%
8%
4%
7%
Gross Payout at Maturity
Gross Payout at Maturity
8%
Index
10%
2%
0%
-2%
-4%
5%
4%
3%
2%
-8%
1%
Dec-13
Dec-14
HSCEI vs HSI 6M ATM Outperformance
6%
-6%
-10%
Dec-09
Dec-10
Dec-11
Dec-12
HSCEI vs HSI 6M ATM Outperformance Contingent on Both Indices Higher at Expiry
0%
Dec-09
Dec-10
Dec-11
Dec-12
Dec-13
Dec-14
In addition, investors can consider overlaying a contingent feature on the outperformance option for additional savings. For
example, a 6-month ATM call option on the outperformance of HSCEI over HSI contingent on both indices higher at expiry
would give the same payout as the corresponding outperformance option at maturity as long as both equity indices rise
above their spot level at the end of the 6-month period. Indicatively, this option structure can be purchased at 3.2%
premium.
Figure 97 and Figure 98 show the backtest results of 6M call switch and outperformance option strategies. While the call
switch strategy is more risky than the outperformance option, the option premium outlay for the call switch strategy is also
substantially lower. Outperformance options contingent on both equity legs higher at expiry provide around 27% savings to
the corresponding outperformance option but reduce the probability of gain. Balancing the potential strategy losses, the
general nature of outperformance of HSCEI versus HSI on the upside along with premium cost outlay, we prefer the
outperformance option contingent on both equity legs higher at expiry to implement our China versus Hong Kong
relative value trade.
44
Marko Kolanovic
(1-212) 272-1438
15 December 2014
Cross asset strategy on Korean equity vs. currency correlation breakdown
EM Asia FX likely to weaken further versus USD: Since September 2014, Asia Dollar Index (ADXY <Index>) has fallen
around 3% on the back of stronger DXY, lower policy rates, domestic outflows and intervention. With EM Asia likely
starting the year with rates cuts in China, Korea, Thailand and India, our strategists expect further depreciation of EM Asia
currencies versus the USD across the region in 2015 (see “2015 EM Asia Macro Strategy: Dovish central banks boost
bonds, undermine currencies”, Bert Gochet, 1-Dec-14).
KOSPI 200 vs. USD-KRW correlation has broken down to a 7-year low: KRW depreciated over 9% versus the USD
since September 2014, on the back of the higher USD-JPY view, BOK rate cuts and USD-KRW buying. Despite KRW's
strong fundamentals with Korea’s current account surplus at 6% of GDP, our strategists forecast a further weakening of
KRW with 2Q15 target of 1,160 in conjunction with a USD-JPY target of 125 and 25bp of BOK cuts. Against this
backdrop, the correlation between Korean equities and USD-KRW has fallen sharply to a level unseen since 2007 (Figure
30). We believe this dynamic will persist in 2015, likely resulting in higher equities and weaker currency in Korea.
To implement the diverging equity vs. currency view in Korea, investors can consider a strategy of going long a quanto
USD call and short struck USD call on KOSPI 200. The payoff of quanto USD options is based on underlying return in
local currency while the payoff of struck USD option is based on underlying return in USD. Hence, this strategy will
generate a profit if KOSPI 200 rises while KRW depreciates vs. USD – see Table 10 for the payoff scenario analysis.
Indicatively, the following structures can be offered at a zero cost: 1) long ATM quanto USD call and short 100.5% struck
USD for a 6-month tenor; or 2) long ATM quanto USD call and short 101.5% struck USD for 1-year tenor.
Table 10: Payoff scenario analysis of long KOSPI 200 6M ATM quanto USD call and short 6M 100.5% struck USD call
Figure 99: Weak correlation between KOSPI 200 vs. KRW-USD is likely
to persist in 2015 driven by JPY-KRW and potential further BoK easing
Figure 100: Long quanto vs. short struck call strategy can generate
profits when equity-FX correlation breaks down
Correlation
Net Payoff %
Option Payoff %
45
Marko Kolanovic
(1-212) 272-1438
15 December 2014
Long India low oil beneficiaries with smart hedging
Continued low oil price bodes well for Indian equities: 2015 is set to be the third consecutive year that oil demand
growth is eclipsed by strong non-OPEC supply growth. Our commodities strategists forecast an average Brent price of
$82/bbl and WTI $77.25/bbl in 2015. The OPEC meeting on November 27 where members decided not to cut oil
production reaffirms our expectation that Brent will likely trade under $70/bbl in the coming months. Correcting oil and
commodity prices constitute a large, positive terms of trade shock to India. The CAD is forecast to fall to 1.3% of GDP and
lower if oil prices stay at current levels (“India in 2015: elephant at the crossroads?”, Sajjid Chinoy, 4-Nov-14), which is
likely to provide further headwinds in Indian equities (Figure 101).
While the oil price correction may have been largely priced in, if oil prices stabilize around these levels, the real impact and
further upside could materialize for the low oil price beneficiaries over the coming quarters. Investors can target such an
exposure using J.P. Morgan India Low Oil Beneficiaries Basket <JPHINLOI> which consists of the stocks whose share
price moves show the most negative correlation with oil price moves historica lly. The basket has a correlation of -0.08
against Brent price moves based on the past 5-year monthly return data. Indicatively, total return swaps on JPHINLOI can
be offered at 3M USD Libor + 110bps with execution fees of 25bps in/25bps out and 100% dividend pass through.
Figure 101: Indian equities have low correlation with oil prices
Re-based Index Level
Table 11: Composition of India Low Oil Beneficiaries Basket (JPHINLOI)
US$/bbl
*The past performance of JPHINLOI Index is simulated based on the index weightings as of
December 5, 2014 and is not indicative of future returns. All price performance excludes
commissions and fees.
*J.P. Morgan India Low Oil Beneficiaries Basket <JPHINLOI> consists of 20 stocks whose stock
price moves show the most negative correlation with the oil price moves (based on the past 5 year
monthly data) among the MSCI India IMI universe with average daily turnover greater than USD
10mn. Assuming 1/3 of the 3-month average daily turnover of constituent stocks, the basket trades
USD 73mn/day.
Meanwhile, it may be prudent to have some hedging established in the Indian equity portfolio given the strong performance
and consensus overweight positioning in Indian equities. While many investors prefer using futures for cost reasons,
hedging via short futures can deteriorate the risk/return profile of the portfolio as shown in Figure 102. Comparing the
systematic strategies via short NIFTY futures versus long NIFT Y 1M puts, put hedging (both outright puts and put spreads)
have higher average monthly net returns than futures hedging. Despite the cost benefit, short futures can result in significant
losses in market rallies, such as the rally followed by the QE tapering shock in May 2013 and pre-election rally in 2Q14.
With NIFTY short-term implied volatility currently trading at historical low levels, close to those of developed
markets, investors may want to use NIFTY puts or put spreads for hedging their long India n equity portfolio while
maintaining upside exposure, perhaps selectively via low oil beneficiaries stocks mentioned above.
Additionally, investors can also consider applying various signals to the systematic put overlay strategy. One simple
example we present in Figure 103 is a “reversal signal” based on the 1-month z-score of NIFTY benchmark index, by which
put spread overlay positions are rolled over only if the z-score is positive and otherwise no hedging positions are initiated.
Combining this signal would have improved the performance of the hedged portfolio by not initiating the hedging positions
when the market is expected to rebound after a correction and hence leading to cost savings.
46
Marko Kolanovic
(1-212) 272-1438
15 December 2014
Figure 102: Monthly hedging performance via NIFTY futures andput
options (based on monthly data from Jan-12 to Nov-14)
Figure 103: Combining a reversal signal* with systematic put spread
overlay would have improved the performance (based on monthly data
from Jan-12 to Nov-14)
Rebased performance
Note: Monthly returns are calculated assuming 1M puts were rolled one day prior to the expiry.
*The reversion signal is determined by the 1M z-score of NIFTY price index calculated as (NIFTY
current level – NIFTY 1M average) / (NIFTY 1M stdev). The red line represents the performance of
a strategy of rolling into new put spread overlay positions only if the z-score is positive (otherwise
no put spread overlay) while the blue line represents the performance of systematic put spread
overaly.
Note: Monthly returns are calculated assuming futures and 1M puts were rolled one day prior to
the expiry. *No. of months when put option strategies outperformed a short futures strategy.
47
15 December 2014
Marko Kolanovic
(1-212) 272-1438
Relative value between the European and US energy sectors
The US and European energy sectors have both suffered severe losses following the collapse of oil prices. The US Energy
sector (XLE) and the European Energy sector (SXEP Index) tracked each other relatively well at the start of the year.
However, their performance differential in US Dollar terms have diverged substantially since June, leading to an overall
YTD underperformance of 12% for SXEP relative to the XLE ETF in US Dollar price terms.
Figure 104: Performance of the STOXX Energy sector relative to the
XLE ETF
Figure 105:The XLE less SXEP vol spread has picked up again, but is
not as wide as in the October correction
SXEP vs. XLE price performance (rebased 31-Dec-13)
XLE less SXEP 6M ATM volatility spread
10%
0%
Aug-14
70
Apr-14
2%
XLE less SXEP 6M ATM vol spread
Dec-12
80
Oct-14
4%
Aug-14
90
Jun-14
6%
Apr-14
100
Feb-14
8%
Dec-13
110
Dec-13
SXEP
Aug-13
XLE US
Apr-13
120
Fundamentally, the European and US energy sector indices show substantial differences, with a much higher weight in
services and in exploration in the US relative to Europe. Services and exploration companies are most exposed to the
current environment of low oil prices, as their main clients are integrated oil and gas companies which are cutting capex. In
the SXEP index, integrated oil and gas makes up 85% of the index, while the sum of exploration and services account for
approximately 10% of the weight; in XLE the weight of integrated oil is just 35%, and exploration and services combined
are just shy of 50% of the index (Figure 106 and Figure 107). We recommend investors to buy 1.25x Jun-15 ATM SXEP
calls and sell 1x XLE Jun-15 ATM calls for zero cost to play the relative value between the two indices.
Figure 106:SXEP sub-industry breakdown, integrated Oil and Gas
makes up 85% of the index
Exploration
Refining &
Other, 2.2%
& Produc,
Marketing,
3.4%
0.5%
Drilling,
1.4%
Equipment &
Services,
7.3%
Refining &
Marketing,
7.9%
Drilling,
2.6%
Storage &
Transport,
7.4%
Integrated
Oil & Gas,
85.2%
Figure 107: XLE sub-industry breakdown, integrated Oil and Gas
makes up only 35% of the index
Exploration
&
Production,
28.6%
48
Coal &
Consumable
Fuels, 0.9%
Integrated
Oil & Gas,
34.8%
Equipment &
Services,
17.8%
Marko Kolanovic
(1-212) 272-1438
15 December 2014
Trading US Financials outperformance via call switches, basket
The Financials sector (ex bond-proxy REITs) is one of our highest overweight conviction ideas on the expectation that
rising interest rates will be a significant catalyst for outperformance in 2015. We recommend our top trade ideas for going
long the sector in 2015.
Financials vs. Materials call switch - J.P.Morgan US Equity Strategist Dubravko Lakos-Bujas recommends an OW in
Financials and UW in Materials heading into 2015, while Materials implied volatility is trading at its largest premium to
Financials volatility this cycle. To position for our Strategists’ sector outlook for 2015 while taking advantage of these
volatility dislocations, we recommend buying a Jun-15 Financial Sector ETF vs. Materials Sector ETF ATM call
switch (i.e. sell a Jun-15 ATM Materials Sector call to buy a Jun-15 ATM Financials sector call). At current levels, this
trade can be indicatively entered into for a net 50bps up-front credit (or can be made approximately premium neutral by
shifting the Materials call strike a bit more than 1% OTM). We see the following fundamental supports for the Financials
sector:

Financials are a play on rising rates, as the sector is among the strongest performers around an initial Fed rate hike.

Financials are sensitive to an improving labor market, as declining unemployment improves loan growth.

The sector is a predominantly domestic play, with 80% of revenues coming from the US. This should help the sector
outperform in a strong USD environment, relative to export oriented sectors (like Materials).

Financials have the 3rd cheapest forward P/E among US sectors (only Energy and Telecoms are cheaper), and trades
at a 2 turn discount to the S&P 500. The sector is also expected to drive 36% of US earnings growth next year.
By contrast, we see the following reasons for a bearish relative view on Materials:

The Materials sector has high foreign revenue exposure, and the strongest negative correlation to the US dollar
among sectors (even higher than Energy).

Rising rates are a negative for Materials, given the capital intensive nature of their business.

Significant demand for the sector is driven by China, where investment spending as a % of GDP is expected to
decline steadily.

Materials companies have few available levers to lower costs and improve productivity.

Materials trade at a valuation premium to the S&P 500, and is the 4th most expensive sector on a forward P/E basis.
Meanwhile, Financials volatility is trading near cycle lows (Figure 108), and at its largest discount to Materials volatility
this cycle (Figure 109). The discount to Materials implied volatility is also larger than the 6M realized vol discount at any
point in the last 7 years. In other words, if you went long 6M Financials and short Materials volatility at current levels, you
wouldn't have lost money based on subsequent 6M realized volatility at any point since 2008.
49
15 December 2014
Marko Kolanovic
(1-212) 272-1438
Figure 108: Financials implied vol is near its lowest level since
2007…
Figure 109: … and is trading at its largest discount to Materials
sector volatility this cycle
12%
50%
45%
9%
Financials sector ETF
6M ATM implied vol
40%
35%
30%
3%
25%
0%
20%
-3%
15%
10%
2010
Financials-Materials
6M ATM Spread
6%
2011
2012
2013
-6%
2009
2014
2010
2011
2012
2013
2014
Buy J.P. Morgan US Financials Basket - investors who want to zero in on top Financial stock picks for 2015 can consider
going long the J.P. Morgan US Financials Basket. This basket provides exposure to Financial companies that J.P. Morgan
fundamental equity analysts believe are best positioned to outperform in a rising interest rate environment. The basket
contains 13 companies and can be accessed on Bloomberg via ticker JPAMFINL <Index>. Investors can also consider
buying calls on the basket - currently, Jan’16 ATM calls on the J.P. Morgan US Financials Basket can indicatively be
bought for 9.2% of notional.
Figure 110: Composition of the J.P. Morgan US Financials Basket – JPAMFINL <Index>, as of December 12th 2014
-5.5%
$44,938
$204
0.5%
10.4%
N/A
1.14
10.7%
1.7%
1.6%
13.1%
0.76
2.7%
0.7%
1.8%
13.9%
0.94
0.9%
1.5%
1.9%
10.3%
15.0%
1.34
13.4%
5.1%
N/A
$78
-9.1% -13.0%
-0.9%
1.01
2.3%
1.8%
3.2%
$28,030
$159
-6.4%
-0.6%
19.4%
2.28
4.9%
1.5%
4.6%
$14,291
$108
-1.9%
0.6%
10.1%
0.83
6.0%
1.2%
2.9%
$4,130
$39
-2.3% -12.0%
-1.5%
3.88
9.3%
2.3%
4.5%
7.8%
$60,006
$320
-4.2%
-4.2%
5.9%
0.83
5.1%
2.5%
N/A
$10.0
7.8%
$13,779
$166
-1.5%
-2.8%
7.0%
0.79
1.9%
1.8%
2.5%
$36.0
7.8%
$37,541
$222
-0.1%
-2.4%
17.0%
2.97
19.1%
0.8%
-0.7%
$108.5 $140.0
7.8%
$5,516
$43
-5.0%
-6.3%
8.5%
1.81
3.7%
N/A
N/A
-1.6%
1.4%
15.1%
2.0%
2.3%
-0.2%
3.6%
16.3%
1.8%
1.6%
OW
$15.1
$18.5
7.0%
N
$39.9
$39.0
7.8%
Vivek Juneja
OW
$17.1
$18.0
7.8%
$180,147 $1,364
Richard Shane Jr
OW
$80.2
$95.0
7.8%
$44,572
$243
N
$87.1
$84.0
7.8%
$29,332
OW
$44.4
$56.0
7.8%
N
$61.8
$65.0
N
$55.0
$62.0
OW
$41.8
$50.0
OW
$52.8
N
ARCC
ARES CAPITAL COR
Asset Management & Custody Ban Richard Shane Jr
BK
BANK NY MELLON
Asset Management & Custody Ban Vivek Juneja
BAC
BANK OF AMERICA
Diversified Banks
COF
CAPITAL ONE FINA
Consumer Finance
CME
CME GROUP INC
Specialized Finance
Kenneth B Worthington
CMA
COMERICA INC
Diversified Banks
Steven Alexopoulos
DFS
DISCOVER FINANCI
Consumer Finance
Richard Shane Jr
LNC
LINCOLN NATL CRP
Lif e & Health Insurance
Jimmy S Bhullar
LPLA
LPL FINANCIAL HO
Investment Banking & Brokerage
MET
METLIFE INC
Lif e & Health Insurance
Jimmy S Bhullar
RF
REGIONS FINANCIA
Regional Banks
Vivek Juneja
SCHW
SCHWAB (CHARLES)
Investment Banking & Brokerage
SIVB
SVB FINANCIAL GR
Regional Banks
Steven Alexopoulos
SPX
S&P 500
50
0.89
1Y Fwd
EPS
Grow th
6.7%
Price
Mkt. Cap
Wgt (%)
Target
($M)
Industry
3M
Price
Name
S5FINL S&P 500 FINANCIALS
1M
$4,752
3M
ADV
($M)
$34
Rating
Tick er
Analyst
N
OW
Price Momentum
12M
1Y Fw d
P/B
-6.5%
-4.1%
0.5%
23.8%
-0.6%
2.3%
-1.7%
-0.6%
$144
2.3%
$7,973
7.8%
7.8%
7.5%
$63.0
$10.0
$28.8
Div
Yield
Buyback
Yield
15 December 2014
Marko Kolanovic
(1-212) 272-1438
Get on board the US Airlines industry
Although the domestic Airlines industry has been a strong performer over the last three months (Top US Airlines +25%,
Transports +11%, Industrials +3.5%, SPX +2.5%), J.P.Morgan US Equity Strategist Dubravko Lakos-Bujas picked Airlines
as a top thematic idea for 2015. Attractive valuation, a lift from increasing corporate/consumer spending, cheap fuel and
potential margin expansion are all reasons to favor the industry in 2015. For details on our rationale and for Airlines analyst
Jamie Baker's positive fundamental views, please refer to pgs 109-112 of the US Equity Markets: 2015 Outlook report.
Buy J.P. Morgan US Airlines Basket – the basket provides exposure to a portfolio of Airlines companies that derive the
majority of their revenues domestically. Underlying constituents need to be greater that $1B in market-cap and trade at least
$10M in ADV, measured over the last three months. The basket contains 9 companies and can be accessed on Bloomberg
via ticker JPAMAIRL <Index>. Investors can also consider buying calls on the basket - currently, 6M ATM calls on the
J.P. Morgan US Airlines Basket can indicatively be bought for 11% of notional.
Figure 111: Composition of the J.P. Morgan US Airlines Basket – JPAMAIRL <Index>, as of December 12th 2014
Name
Analyst
ALASKA AIR GROUP
Jamie Baker
UW
$55.8
$62.0
5.0%
$7,402
$84
-0.4% 18.3% 56.0%
11.4
1Y Fwd
EPS
Growth
19.8%
ALLEGIANT TRAVEL
N/A
NC
$135.5
N/A
1.6%
$2,369
$21
1.2%
29.3%
16.5
38.2%
AMERICAN AIRLINE
Jamie Baker
OW
$50.0
$80.5
24.2%
$35,842
$742
15.1% 33.1%
N/A
6.2
DELTA AIR LI
Jamie Baker
OW
$47.7
$73.0
27.0%
$39,905
$739
9.9%
20.4% 70.4%
JETBLUE AIRWAYS
Jamie Baker
N
$14.8
$18.5
2.9%
$4,322
$142
SOUTHWEST AIR
Jamie Baker
N
$41.4
$52.0
19.0%
$28,107
$401
SPIRIT AIRLINES
N/A
NC
$68.1
N/A
3.3%
$4,957
$95
UNITED CONTINENT
Jamie Baker
OW
$64.1
$95.5
16.0%
$23,657
$427
17.4% 27.2% 70.4%
VIRGIN AMERICA I
N/A
NC
$33.8
N/A
1.0%
$1,450
$154
Rating
Price
Price
Mkt. Cap
Wgt (%)
Target
($M)
3M ADV
($M)
Price Mom e ntum
Div Yield
Buyback
Yield
0.9%
1.8%
N/A
3.4%
40.9%
0.4%
N/A
10.7
37.9%
0.6%
N/A
18.2% 21.5% 68.9%
12.3
67.5%
N/A
-0.2%
5.3%
22.4% 122.0%
15.3
38.6%
0.5%
1.6%
-13.1% -2.9% 57.1%
15.0
41.9%
N/A
0.0%
8.5
52.2%
N/A
-0.1%
N/A
N/A
N/A
N/A
1M
3M
7.8%
12M
1Y Fwd
P/E
N/A
N/A
N/A
S&P 500
-1.6%
1.4%
15.1%
2.0%
2.3%
S&P 500 INDUSTRIALS
-2.9%
1.9%
12.0%
2.1%
3.1%
S&P 500 TRANSPTN
-1.8%
9.5%
32.6%
1.5%
3.8%
Source: J.P. Morgan Equity Derivatives Strategy, Bloomberg. Note on non-covered companies: This basket has been created to leverage the theme of this research report. It includes companies
that are not covered by J.P. Morgan Research (marked “NC”) and should not be viewed as a recommendation with respect to these companies
Stock replacements on “high-fliers” with relatively cheap vol – investors concerned with the swift rise in Airlines stocks
can consider booking profits on the underlying shares and replacing them with long calls. In spite of the recent pickup
in single-stock Airline vol, it has retraced from the October spike to pre-Ebola levels, and remains cheap compared to
historical levels (3M ATM implied vol on each of the major airlines is currently trading lower than its median value
measured over the last 3 years). Delta (DAL), in particular, looks like an attractive candidate for a stock replacement
strategy, given its relatively cheap vol and the fact that the underlying shares are up over 20% over the last 3 months, and
over 70% over the last 12 months.
Figure 112: Delta (DAL) 3M ATM implied vol looks relatively cheap vs. history
Avg daily
3M ATM
Last
notional
3M ATM implied vol
Ticker
Airline
Price
traded ($M) implied vol (3Y %ile)
DAL equity DELTA AIR LI
48.33
$193.0
40.5 %
14.0 %
LUV equity SOUTHWEST AIR
41.92
$42.7
37.4 %
21.7 %
SAVE equity SPIRIT AIRLINES
69.00
$13.1
45.2 %
25.8 %
JBLU equity JETBLUE AIRWAYS
15.29
$13.9
46.6 %
37.4 %
UAL equity UNITED CONTINENT
65.80
$164.7
46.4 %
38.1 %
AAL equity AMERICAN AIRLINE
50.53
$311.6
44.7 %
81.7 %
Source: J.P. Morgan Equity Derivatives Strategy, Bloomberg. Note: AAL data goes back only till 12/09/13
51
15 December 2014
Marko Kolanovic
(1-212) 272-1438
Contrarian US Energy trade ideas
Heading into a year in which oil is expected to remain low, we suggest contrarian Energy trade ideas based on sector
technicals, investor positioning and company fundamentals. For additional details, please refer to pgs 113-116 of the US
Equity Markets: 2015 Outlook report.
Buy call spreads on Energy Sector ETF to position for potential (non-consensus) rebound – as WTI crude broke $60
recently, retreating to levels last seen in 2009, the Energy sector continued its downward spiral and is the only S&P 500
sector in negative territory this year. While we are not calling for a bullish crude oil environment in 2015, we note that
investor positioning and seasonality technicals point to a recovery in the underlying sector if oil prices start to stabilize.
Most recent reported NYMEX net non-commercial futures positions in WTI crude look like they ticked up after a sustained
decline since the summer (Figure 113). After the recent decline, Energy is slowly becoming a Value sector and would stand
to benefit in 1H'15 if strong Value seasonal effects occur again (Figure 114).
Figure 113: WTI oil futures price vs. investor positioning
contracts (000s), net noncommercial futures positions
500
WTI front month price
Figure 114: Energy Beta-adjusted returns and Value seasonality
$/bbl
110
450
100
S&P 500 Top Quintile Value
S&P 500 Energy
2.0%
1.5%
1.0%
400
90
350
80
Net long positions
300
70
250
0.5%
0.0%
-0.5%
Jan
Feb
Mar
Apr May
Jun
Jul
Aug
Sep
Oct
Nov
Dec
-1.0%
200
Dec-13
60
Feb-14
Apr-14
Jun-14
Aug-14
Oct-14
-1.5%
With 6M ATM implied vol on the major Energy Sector ETF currently trading at its highest point over the last 2 years, it is
relatively expensive for contrarian investors to buy calls to position for a rebound in the Energy sector. Upside skew (as
measured by the 6M 100/115% skew) is relatively flat and trading in only its 26th percentile measured over the last 2 years,
which makes call spreads attractive. Currently, a 6M 100/120 call spread on the major Energy Sector ETF can
indicatively be bought for 6.2% of notional, offering a maximum reward/risk of ~3.2x.
Buy J.P. Morgan US Energy Basket – the basket provides exposure to high-quality/ turn-around Energy companies that
declined along with the broader Energy sector weakness, and which J.P. Morgan fundamental equity analysts believe are
best positioned to outperform in a depressed oil environment. The basket contains 11 companies and can be accessed on
Bloomberg via ticker JPAMENRG <Index>. Investors can also consider buying calls on the basket - currently, 6M ATM
calls on the J.P. Morgan US Energy Basket can indicatively be bought for 10% of notional.
Figure 115: Composition of the J.P. Morgan US Energy Basket – JPAMENRG <Index>, as of December 12th 2014
Ticker
Name
APC
BWP
Industry
Price
Mkt. Cap
Wgt (%)
Target
($M )
3M ADV
($M)
Price Mom entum
12M
1Y Fw d
P/E
-9.0%
23.6
-32.7%
1.3%
-0.2%
-8.4% -16.6% -34.5%
15.7
6.5%
2.5%
N/A
4.2%
25.3
-34.2%
0.6%
N/A
N/A
41.0
22.7%
N/A
N/A
-12.0% -15.6% 11.8%
21.9
-25.8%
0.6%
N/A
$26
-10.3% -15.8% 53.7%
19.0
17.9%
2.6%
N/A
$137
-19.1% -35.0% -32.7%
19.7
-7.1%
1.5%
-0.3%
$4,246
$34
-11.7% -18.6% 16.1%
21.5
19.7%
8.2%
N/A
$36,355
$311
-8.6% -19.9%
-3.4%
9.3
13.9%
2.8%
5.0%
$19,543
$302
-24.0% -35.8% -25.9%
26.3
-4.9%
0.1%
N/A
$14,708
$45
-14.7% -22.7%
39.1
33.3%
2.8%
N/A
16.6%
2.0%
2.3%
-12.7% -18.8% -8.6%
2.9%
2.7%
Rating
Pr ice
ANADARKO PETROLE Oil Comp-Explor&Prodtn Joseph D Allman
OW
$73.3
$95.0
19.1%
$37,143
$459
-18.8% -29.7%
BOARDWALK PIPELI
Pipelines
OW
$15.8
$24.0
2.0%
$3,845
$19
XEC
CIMAREX ENERGY C
Oil Comp-Explor&Prodtn Joseph D Allman
OW
$98.5
$125.0
4.4%
$8,594
$148
-14.8% -27.1%
DM
DOMINION MIDSTRE
Pipelines
OW
$33.0
$43.0
1.1%
$2,110
$18
-7.1%
EOG
EOG RESOURCES
OW
$86.4
$109.0
24.3%
$47,332
$544
EQM
EQT MIDSTREAM PA
Pipelines
OW
$81.4
$109.0
2.6%
$5,040
NBL
NOBLE ENERGY INC
OW
$43.9
$60.0
8.1%
$15,871
NS
NUSTAR ENERGY LP
Pipelines
Jeremy Tonet
OW
$54.5
$74.0
2.2%
PSX
PHILLIPS 66
Oil Comp-Integrated
Phil M Gresh
OW
$65.7
$89.0
18.7%
PXD
PIONEER NATURAL
OW
$131.3
$201.0
10.0%
PAGP
PLAINS GP HOLD-A
Pipelines
OW
$24.3
$35.0
7.6%
SPX
S&P 500
S5ENRS S&P 500 Energy
Source: Bloomberg, J.P. Morgan estimates.
52
Analys t
Jeremy Tonet
Jeremy Tonet
Jeremy Tonet
Jeremy Tonet
1M
0.0%
3M
N/A
2.4%
0.2%
1Y Fw d EPS
Buyback
Div Yield
Grow th
Yield
15 December 2014
Marko Kolanovic
(1-212) 272-1438
ECB Sovereign QE: get upside exposure to Euro zone Banks
The Banks sector is the one that would benefit the most from an announcement of Sovereign QE from the ECB, which our
economists are forecasting will come in the January 22nd meeting following the ECJ ruling on the legality of Sovereign QE.
The announcement of Sovereign QE, which in our economists’ view will happen contextually to the purchase of nonfinancials corporate bonds and to several TLTRO terms improvements, should re-ignite the marginal investors’ interest in
Euro zone Banks (e.g. US fast money). Furthermore, Sovereign QE will also favor equities indirectly, keeping downward
pressure on the Euro and causing a further compression of Peripheral spreads. Our EMEA equity strategy team is OW banks
and highlights that dilution and balance sheet concerns should be largely behind us, while Banks' cost of funding should
improve further.
Derivatives markets are partly pricing in QE expectations, and demand for the SX7E upside has led the SX7E to trade with
one of the flattest call skews globally (Table 12), while the SX7E volatility terms structure is firmly inverted (Figure 116).
With the ECB intervention mostly likely materializing in the first half of the year, we like playing the upside theme for
Eurozone banks through Jun-15 options.
Table 12: SX7E 6M call skew is among the flattest globally and at
multi-year lows
6M 100110%
Skew
Figure 116: The SX7E ATMF volatility term structure is firmly inverted,
while Euro STOXX 50 term structure is currently approximately flat
ATMF implied volatility term structures
Current
5Y
%ile
Avg
Max
Min
SPX
3.8%
75%
3.4%
4.5%
1.9%
SX5E
2.1%
14%
2.7%
4.7%
1.5%
UKX
2.8%
51%
2.8%
4.5%
1.0%
DAX
2.4%
13%
2.9%
4.5%
1.9%
SMI
2.4%
69%
2.1%
3.4%
0.7%
NKY
0.8%
43%
1.3%
4.3%
-0.8%
HSI
-0.2%
1%
1.1%
3.6%
-0.3%
KOSPI2
0.1%
3%
1.3%
3.3%
-0.1%
AS51
2.7%
83%
2.1%
3.5%
0.7%
EEM
2.1%
8%
2.7%
4.1%
1.5%
SX7E
1.0%
0%
2.3%
4.5%
0.9%
32%
SX7E
Euro STOXX 50
28%
24%
20%
16%
Jan-15
Mar-15
May-15
Jul-15
Sep-15
Nov-15
We recommend long SX7E Jun-15 150/165 call spreads, financed by selling 125 strike puts for a premium intake of
1.9% (SX7E spot ref. 138.19, approx. 50% delta). In our base case, there is limited downside to Euro zone banks as long as
the 'Draghi put' remains credible. We therefore think that the risk reward profile for funding this structure via the sale of a
put is favorable, as SX7E volatility remains expensive and despite the relatively flat put skew. For reference a SX7E ATM
Jun-15 call option costs approximately 6.9%.
An alternative for investors that are less sanguine about the limited downside risk is to buy the SX7E Jun-15 150/165
call spread without selling the put. This structure costs approximately 2.4% and offers a cost-to-payout ratio of 4.6 due to
the exceptionally flat call skew.
The announcement of Sovereign QE and the expansion of the ECB balance sheet will likely put downwards pressure on the
EUR/USD, making call options on the SX7E contingent on a decline in the EUR/USD a neat way to play this catalyst. A
SX7E Jun-15 110% call conditional on EUR/USD < 1.2 costs just 2.35%, offering a discount to vanilla option of 34%.
The discount is higher for a similar structure on the Euro STOXX 50 rather than on the SX7E (~47%), due to the higher
liquidity of Euro STOXX 50 volatility and to the different pricing of equity/FX correlation.
53
Marko Kolanovic
(1-212) 272-1438
15 December 2014
Trade our top US 2015 thematic stock ideas via baskets
In addition to baskets tracking the top Airlines, Energy and Financial picks for 2015, our US equity strategists also
recommended baskets tracking stocks with attractive total yield, and high domestic revenue exposure.
J.P. Morgan US Sustainable Shareholder Yield Basket (JPAMSYLD <Index>)
JPAMSYLD <Index> contains 25 names and provides exposure to a portfolio of shareholder-friendly S&P 500 companies
with attractive total yield and strong cash flow generation.
J.P. Morgan Domestic Revenue Exposure Basket (JPAMDREV <Index>)
JPAMDREV <Index> contains 42 names and provides exposure to a diversified portfolio of S&P 500 companies that derive
the bulk of their revenues domestically.
In the U.S. Year Ahead 2015 publication, J.P. Morgan equity analysts identified key drivers of sector stock prices and
picked targeted investment ideas suited to various investment strategies: growth, value, income-oriented, shorting, and
market neutral. We launched five baskets that investors can use to gain exposure to these ideas.
J.P. Morgan US 2015 Top Picks Basket (JPUSTP15 <Index>)
JPUSTP15 <Index> contains 48 names and provides exposure to a selection of US stocks that J.P.Morgan Equity Research
analysts have chosen as their top overall pick for investors in 2015.
J.P. Morgan US 2015 Growth Picks Basket (JPUSGP15 <Index>)
JPUSGP15 <Index> contains 48 names and provides exposure to a selection of US stocks that J.P.Morgan Equity Research
analysts have chosen as their top Growth pick for investors in 2015.
J.P. Morgan US 2015 Value Picks Basket (JPUSVP15 <Index>)
JPUSVP15 <Index> contains 42 names and provides exposure to a selection of US stocks that J.P.Morgan Equity Research
analysts have chosen as their top Value pick for investors in 2015.
J.P. Morgan US 2015 Income Picks Basket (JPUSIP15 <Index>)
JPUSIP15 <Index> contains 23 names and provides exposure to a selection of US stocks that J.P.Morgan Equity Research
analysts have chosen as their top Income pick for investors in 2015.
J.P. Morgan US 2015 Short Picks Basket (JPUSSP15 <Index>)
JPUSSP15 <Index> contains 11 names and provides exposure to a selection of US stocks that J.P.Morgan Equity Research
analysts have chosen as their top Short pick for investors in 2015.
Table 13: Derivative pricing for J.P. Morgan Top US 2015 Thematic Stock Baskets11
Basket
Sustainable Shareholder Yield
Revenue Exposure
Top Picks
Growth Picks
Value Picks
Income Picks
Short Picks
Ticker
1Y ATM Call*
JPAMSYLD
JPAMDREV
JPUSTP15
JPUSGP15
JPUSVP15
JPUSIP15
JPUSSP15
6.75%
9.35%
10.10%
9.90%
9.65%
6.45%
8.85%
1Y Risk Reversal
(# of ATM calls per ATM put)*
1.30
1.12
1.04
1.02
1.05
1.31
1.23
Source: J.P. Morgan Equity Derivatives Strategy. *Options on a reduced basket of the most liquid names screened for both spot and volatility liquidity. Indicative pricing
11
All pricing is indicative, please contact us for firm prices
54
15 December 2014
Marko Kolanovic
(1-212) 272-1438
Europe thematic investment via TRS, basket and single stock options
In Table 14 below we highlight ways to gain exposure to the J.P. Morgan 2015 European thematic baskets. These baskets
have been put together by our equity strategists to capture their major 2015 themes. More details can be found in "Equity
Strategy: Year Ahead 2015 - Upside is not exhausted yet; Look for a rotation in regional drivers”.
J.P. Morgan '15 Eurozone recovery basket
P/E lower relative to the market than in the summer of 2012, at the height of the Eurozone crisis. Screened for stocks that
have significant domestic exposure (>30%) and are most positively correlated to Euro area PMIs
J.P. Morgan basket of beneficiaries of lower oil/commodity prices
The fall in oil and other commodity prices is a welcome development for final demand, boosting real disposable incomes
and purchasing power. Lower commodity prices are a positive for Transport, Airlines, Autos, Retail, Travel and Leisure.
J.P. Morgan basket of sustainable yield plays
Screened for stocks with sustainable dividend yield growth since 2006 and 15e dividend yield <3%.
J.P. Morgan basket of buyback stocks
Screened for stocks that are conducting or are expected to do share buybacks.
J.P. Morgan basket of Euro exporters
Euro exporters are likely to benefit from a weaker EUR/USD. Screened for stocks with significant international exposure
(>50%) and are most negatively correlated to the Euro.
Table 14: Derivative pricing for J.P. Morgan 2015 Europe thematic baskets12
Basket
Eurozone Recovery
Commodity Winners
Sustainable Yield Plays
Buyback Stocks
Euro Exporters
Ticker
JPDEER15
JPDECW15
JPDEDP15
JPDEBB15
JPDEEX15
1Y Total Return
Swap
3M€ + 38bps
3M€ + 38bps
3M€ + 41bps
3M€ + 49bps
3m€ + 38bps
1Y ATM
Call*
7.45%
7.75%
6.00%
6.00%
7.15%
1Y Risk Reversal
(# of ATM calls per ATM put)*
1.30
1.10
1.24
1.21
1.16
Source: J.P. Morgan Equity Derivatives Strategy, J.P. Morgan Equity Strategy. *Options on a reduced basket of the 10 most liquid names for each basket. Indicative pricing
2015 baskets single stock call spread candidates
In Table 15 below we list optionable names in the Eurozone recovery and Exporters baskets and highlight attractive cost to
payout ratios for Jun15 40/20-delta call spreads.
12
All pricing is indicative, please contact us for firm prices
55
15 December 2014
Marko Kolanovic
(1-212) 272-1438
Table 15: Potential call/call spread candidates from the Eurozone recovery and Exporters baskets. Names with Jun-15 40/20-delta call spreads
with a payout to cost ratio of 4 or higher have been highlighted in bold
Ticker
Name
YTD
Return
YTD 6M
ATM Vol
Change
6M ATM
Vol
Indicative
40 delta
call price*
Indicative
40/20 delta
CS price*
Long/Short
strike
CS payout
to cost
ratio
Call/CS
breakeven
EXPORTERS BASKET
CFR VX
RICHEMONT
0.3%
-2.6%
20.5%
3.9%
2.5%
105%/113%
3.4
108.9%/107.4%
AKZA NA
AKZO NOBEL
-1.4%
-0.5%
22.2%
4.2%
2.7%
104%/112%
3.3
107.7%/106.2%
MT NA
ARCELORMITTAL
-28.6%
1.6%
30.5%
5.5%
3.4%
107%/121%
4.1
112.6%/110.5%
OR FP
L'OREAL
6.6%
-1.6%
19.2%
3.7%
2.3%
103%/111%
3.4
106.7%/105.4%
RI FP
PERNOD RICARD
12.5%
-2.0%
17.9%
3.5%
2.2%
104%/112%
3.3
107.9%/106.6%
AH NA
AHOLD
0.5%
-0.3%
18.0%
3.5%
2.2%
101%/109%
3.4
104.8%/103.5%
REN NA
REED ELSEVIER
27.1%
-0.8%
17.8%
3.4%
2.2%
103%/110%
3.3
106.0%/104.8%
MC FP
LVMH
6.4%
0.0%
20.4%
3.8%
2.4%
104%/112%
3.4
107.8%/106.4%
ASML NA
ASML
28.2%
-0.5%
25.9%
4.9%
3.0%
106%/117%
3.8
110.7%/108.9%
RECOVERY BASKET
G IM
GENERALI
-1.5%
-0.8%
20.8%
3.9%
2.5%
102%/111%
3.3
106.1%/104.7%
CA FP
CARREFOUR
-18.5%
0.0%
27.3%
5.0%
3.1%
104%/116%
3.8
109.5%/107.6%
ADEN VX
ADECCO
-6.2%
-0.3%
22.4%
4.2%
2.6%
103%/113%
3.6
107.3%/105.7%
RNO FP
RENAULT
5.5%
-1.2%
28.6%
5.2%
3.2%
105%/118%
4.0
110.4%/108.4%
AGN NA
AEGON
-11.4%
0.3%
24.0%
4.5%
2.8%
105%/115%
3.7
109.2%/107.5%
UG FP
PEUGEOT
31.8%
-8.6%
33.8%
6.2%
3.8%
110%/127%
4.4
116.4%/113.9%
GLE FP
SOC GEN
-12.9%
1.7%
29.0%
5.2%
3.2%
105%/117%
4.0
109.9%/107.9%
DG FP
VINCI
-6.9%
5.3%
25.1%
4.6%
2.9%
104%/114%
3.5
108.5%/106.8%
HMB SS
H&M
6.1%
0.4%
17.7%
3.4%
2.2%
101%/108%
3.2
104.8%/103.6%
AC FP
ACCOR
4.6%
1.6%
25.2%
4.7%
2.9%
104%/115%
3.5
109.0%/107.2%
UCG IM
UNICREDIT
4.0%
4.1%
34.9%
6.1%
3.8%
108%/123%
3.9
114.2%/111.9%
INGA NA
ING
12.0%
1.5%
27.6%
5.0%
3.1%
107%/119%
3.7
111.9%/110.0%
ENEL IM
ENEL
18.5%
1.3%
26.8%
4.9%
3.0%
107%/118%
3.6
112.0%/110.2%
CAP FP
CAP GEMINI
17.6%
1.7%
27.6%
5.1%
3.2%
106%/119%
4.0
111.0%/109.0%
Source: J.P. Morgan Equity Derivatives Strategy. * Jun-15 options, please contact us for firm pricing. As of 11-Dec-14
56
15 December 2014
Marko Kolanovic
(1-212) 272-1438
Asia thematic investments: reforms of shareholder return enhancement
In 2014, we witnessed constructive efforts in Asia to enhance shareholder returns. Japan led this move by placing
shareholder return enhancement and capital efficiency improvement as the pillars to Japan’s new growth strategy, as a
consensus has been formed that corporate governance must be improved to promote growth and productivity in Japan. The
JPX-Nikkei Index 400, which explicitly uses ROE as a selection criterion, was launched in January 20 14 to achieve this
goal. Along with this development, GPIF reform, the stewardship code and the development of corporate governance code
by TSE have all incentivized companies to improve corporate governance. As a result, we think companies that proactively
focus on improving capital efficiency and shareholder returns will outperform the broader market.
Korea also joined this move as the new Finance Minister Mr. Choi introduced new regulations for Korean corporates to
employ shareholder-friendly capital management and increase their dividend payouts, such as levying the tax on retained
earnings and cutting dividend income tax rates. Although the tax law changes will be effective starting 2015, we have seen a
few companies already moving in that direction, with share buybacks and guidance to increase dividends. Our Korean
strategists believe this structural change remains one of the most important investment themes , potentially leading to a rerating of Korean stocks in the upcoming years.
Investors who want to have exposure to this ongoing development in Japan and Korea can c onsider using JPX-Nikkei 400
Index or J.P. Morgan thematic baskets. J.P Morgan Japan Dividend Payout Basket <JPHJTPOT> consists of 17 stocks
that may raise dividend in the near future beyond the consensus forecast. J.P. Morgan Korea Dividend Boost Basket
<JPHKSDV2> consists of 17 stocks that are likely to increase dividends on the back of the new government initiatives. The
implementation can be done through either equity swaps or options – see Table 16 for the indicative option pricing.
Table 16: Indicative pricing of swaps and options on thematic baskets related to reforms of shareholder return enhancement in Asia
*Option prices on the Korea Divdiend Boost Basket are on the KRW version JPHKSDW2. Pricing as of December 9, 2014.
Table 17: Composition of Japan Dividend Payout Basket <JPHJTPOT>
Ticker
Name
4681 JT
6952 JT
4021 JT
9303 JT
4401 JT
4088 JT
9533 JT
3659 JT
9744 JT
8766 JT
7988 JT
6457 JT
5943 JT
4061 JT
7278 JT
8219 JT
5631 JT
Resorttrust Inc
Casio Computer
Nissan Chem Inds
Sumitomo Warehou
Adeka Corp
Air Water Inc
Toho Gas Co Ltd
Nexon Co Ltd
Meitec Corp
Tokio Marine Hd
Nifco Inc
Glory Ltd
Noritz Corp
Denki Kagaku
Exedy Corp
Aoyama Trading
Japan Steel Work
Curr
Price
2594
1706
2126
642
1438
1809
623
1002
3315
3620
3490
3000
2018
386
2885
2564
420
Mkt Cap
($mn)
2,318
3,966
2,958
1,087
1,288
3,107
2,940
3,721
931
24,075
1,621
1,780
886
1,554
1,212
1,360
1,348
Avg T/O
Index
($mn) Wgt (% )
9.4
7.8
38.2
6.9
14.5
6.7
2.6
6.2
3.0
6.2
5.2
6.1
4.8
6.0
7.0
6.0
2.9
5.9
81.4
5.8
5.6
5.7
6.2
5.5
2.9
5.4
9.5
5.3
3.9
5.0
5.8
4.9
10.2
4.6
* For the details on the basket construction, see ”Equity Derivatives Review: What works in Japan
- Factors backtested”, Michiro Naito, 02-June-2014. Assuming 1/3 of the 3-month average daily
turnover of constituent stocks, the basket trades USD 15mn/day.
Table 18: Composition of Korea Dividend Boost Basket <JPHKSDV2>
Ticker
Name
005930 KP
012330 KP
055550 KP
000270 KP
024110 KP
086280 KP
000810 KP
010130 KP
011210 KP
012450 KP
001680 KP
105630 KP
000100 KP
029780 KP
005300 KP
010120 KP
002270 KP
Samsung Electron
Hyundai Mobis
Shinhan Financia
Kia Motors Corp
Industrial Bank
Hyundai Glovis
Samsung Fire & M
Korea Zinc Co
Hyundai Wia Corp
Samsung Techwin
Daesang Corp
Hansae Co Ltd
Yuhan Corp
Samsung Card Co
Lotte Chilsung
Ls Indus Systems
Lotte Food Co Lt
Curr
Price
1231000
235000
48850
55600
16350
301000
294000
407000
178500
35750
37350
36500
170500
48000
1648000
64800
643000
Mkt Cap
($mn)
165,383
20,864
21,128
20,557
8,239
10,295
12,704
7,005
4,189
1,732
1,172
1,332
1,734
5,072
1,860
1,773
803
Avg T/O
Index
($mn) Wgt (% )
296.6
9.4
50.8
9.4
37.2
9.4
58.3
9.4
20.3
9.4
22.2
9.4
26.7
9.3
15.4
6.0
18.7
6.0
11.5
6.0
7.3
3.0
6.3
3.0
5.3
3.0
4.8
3.0
4.0
1.5
3.6
1.5
2.4
1.5
* For the details on the basket construction, see “J.P. Morgan’s Heart & Seoul: This time it’s
different”, Scott Seo, 29-Jul-14). Note that Hyundai Motors has been removed from the original
basket as the recent KEPCO HQ land purchase raises questions about minority shareholder
treatment and credibility with investors (see “Hyundai Motor Company: Downgrade to Neutral”,
Wansun Park, 18-Sep-14)”. Assuming 1/3 of the 3-month average daily turnover of constituent
stocks, the basket trades USD 53mn/day.
57
Marko Kolanovic
(1-212) 272-1438
15 December 2014
Volatility/Risk Premia Trades
Asia vs. DM volatility spreads - long volatility and carry
Although the phenomenon of Asian volatility and downside skew being suppressed by ongoing structured product issuance
is nothing new, we believe there is value in owning Asia versus DM volatility spreads going into 2015. Not only are the
spreads pricing attractively due to the volatility supply and demand imbalance dynamic, we also have various market
catalysts emerging on the horizon (see Term Structure section) which can lead to significant price swings. On the upside, if
the Asian equity markets rally strongly, the "spot-up, volatility-up” phenomenon due to current derivatives market
positioning will likely lead to volatility spread expansion (see Skew section), both on the implied and realized basis. Should
there be another risk-off event, although the structured product hedging dynamics would initially dampen implied volatility
moves, the realized volatility moves should still provide positive carry against the artificially suppressed implied spread
levels. However, further market decline would likely result in volatility spread expansion as the hedging dynamics around
the embedded barriers in the structured products amplify downside moves. In this scenario, we would expect Asia volatility
to react more violently than DM volatility, as shown in the past historical crisis periods.
In 2014, the Asia versus DM implied volatility spread levels have contracted due to the overall low volatility environment
as well as ongoing volatility supply and demand imbalance on the back structured product issuance. Although there were no
volatility spikes, the spread positions are carrying positively still against the realized levels, which allow investors to be long
volatility and carry without being short tail risks. For the year ahead, we see attractive opportunities in going long H-shares
and KOSPI 200 volatility versus going short S&P 500, FTSE 100, and ASX 200 volatility. For trade implementation, we still
like using vanilla 2Y 80% downside puts with delta hedging rather than using variance swaps in order to 1) avoid the
relatively richer variance convexity of Asia even though the absolute levels have come off; 2) take advantage of the wide
gap in the skews of Asia versus DM; 3) take advantage of the flatter term structures in Asia.
In terms of statistics, based on a combined ranking of implied spreads versus short term/long term realized volatility and
historical entry levels, H-shares versus S&P 500 looks the most attractive, followed by H-shares versus ASX 200 and
KOSPI 200 versus S&P 500. For all the spreads highlighted in Table 19, the carry against short term volatility is positive. In
addition, the implied spreads are all trading at the lowest levels relative to its realized spread history since 2006 which
means that H-shares and KOSPI 200 have been more volatile relative to S&P 500, FTSE 100 and ASX 200 than what
options markets are current pricing in with downside puts for the next two years. Finally, the implied spreads are trading at
low percentiles in their own history over the same period. Hence we believe that the current pricing level provides an
attractive entry point for the spread trades to implement the view of volatility expansion. To avoid concentration risks,
investors can also consider going long an equally weighted basket of H-shares and KOSPI 200 versus going short an
equally basket of S&P 500, FTSE 100 and ASX 200 using 2Y 80% ATMF puts to implement the Asia versus DM volatility
trade.
Table 19: Indicative tradable levels and statistics of various Asia versus DM volatility spreads
2Y 80% ATMF Implied Volatility Spread
2Y Variance Spread
Variance vs Put
2Y Realized Volatility Spread
3M Realized Volatility Spread
Carry (Implied vs 3M Realized)
Put Implied Spread %tile vs Implied History
Put Implied Spread %tile vs Realized History
HSCEI vs HSCEI vs HSCEI vs KOSPI2 KOSPI2 KOSPI2
SPX
UKX
AS51 vs SPX vs UKX vs AS51
2.6%
4.3%
4.9%
-4.0%
-2.3%
-1.7%
9.9%
10.5%
10.2%
2.4%
2.9%
2.7%
7.4%
6.2%
5.4%
6.4%
5.2%
4.4%
8.3%
8.1%
7.9%
1.1%
1.0%
0.7%
8.2%
7.6%
8.0%
-1.3%
-1.9%
-1.5%
5.7%
3.4%
3.2%
2.7%
0.4%
0.3%
8.0%
7.0%
1.2%
12.4%
20.8%
12.4%
0.0%
0.0%
0.0%
0.0%
0.0%
0.0%
Asia vs
DM
0.6%
6.4%
5.8%
4.5%
3.2%
2.6%
6.1%
0.0%
Data as of December 5, 2014. *Asia is equally weighted basket of H-shares and KOSPI 200 and DM is equally weighted basket of S&P 500, FTSE 100 and ASX 200. **History since 2006
58
15 December 2014
Marko Kolanovic
(1-212) 272-1438
The FTSE 100 volatility is subject to different dynamics compared to Asian indices’ volatilities, as structured product
issuance is limited on the FTSE 100 and has been declining over time, while FTSE 100 index realised volatility is typically
suppressed by the strong overwriting flows on the index. This contributed to a single-digit average FTSE 1M realised
volatility in 2014 (9.4%), despite the negative performance of the index (-6.6% YTD at the time of writing) and its
underperformance relative to other global underliers.
The combination of these factors makes the FTSE 100 long-dated volatility a good funding leg for long-dated Asian vol
positions. However, as we discuss in the FTSE hedging section, the upcoming UK parliamentary elections pose a risk, as it
is far from clear that they will lead to a stable coalition and market friendly outcome. Political risk does not derail the trade
prospects in our view, and will likely only temporarily impact the carry of the volatility spread. FTSE long-dated downside
skew is amongst the steepest globally, while Asian index skews tend to be amongst the flattest, making vanilla 2Y 80%
volatility spreads an attractive alternative to var swap spreads, in our view.
Figure 117: Implied and realized volatility spreads of HSCEI vs. SPX
Figure 118: Implied and realized volatility spreads of KOSPI2 vs. SPX
Volatility spread
Volatility spread
45%
20%
2Y 80% ATM Implied Volatility Spread
2Y Variance Spread
Current Entry
40%
35%
30%
2Y Variance Spread
Current Entry
15%
10%
25%
20%
5%
15%
0%
Jan-06
10%
5%
Jan-07
Jan-08
Jan-09
Jan-10
Jan-11
Jan-12
Jan-13
Jan-14
-5%
0%
Jan-06 Jan-07 Jan-08 Jan-09 Jan-10
-5%
Jan-11
Jan-12
Jan-13
Jan-14
-10%
Figure 119: Implied and realized volatility spreads of Asia vs. DM*
Figure 120: Implied and realized volatility spreads of HSCEI vs. UKX
Volatility spread
Volatility spread
25%
2Y Variance Spread
Current Entry
20%
15%
40%
35%
30%
2Y Variance Spread
Current Entry
25%
20%
10%
15%
5%
0%
Jan-06
10%
5%
Jan-07
Jan-08
Jan-09
Jan-10
Jan-11
Jan-12
Jan-13
Jan-14
-5%
* Asia is equally weighted basket of H-shares and KOSPI 200 and DM is equally weighted basket
of S&P 500, FTSE 100 and ASX 200.
0%
Jan-06 Jan-07 Jan-08 Jan-09 Jan-10
Jan-11
Jan-12
Jan-13
Jan-14
59
15 December 2014
Marko Kolanovic
(1-212) 272-1438
S&P 500 vanilla dispersion
S&P 500 implied correlation has traded at an elevated premium to realized correlation for the last couple of years, boosted
by the demand for protection via index options, which drives a large implied-realized vol premium on index options. As we
noted in the first section of this report, volatility risk premia have been generally compressing globally, but S&P 500
index implied to realized, and by extension implied-realized correlation, are among the few equity derivatives risk
premia that haven’t been largely eroded in the last couple of years. For example, 1Y implied correlation is trading at a
~20 correlation point premium to recent realized, and at levels that are higher than realized at any point since the 2H-2011
Eurozone crisis.
As we noted in the Implied Correlation section, sector rotation has contributed to a decrease in index realized correlation
this year, particularly due to Utilities which are traded as a bond/yield proxy. JPM Economists expect the robust economic
growth experienced in the US in the 2nd half of this year to continue into 2015, while our US Equity Strategists remain
constructive on US equities, calling for ~10% upside in the S&P 500, with yield plays (REITs, Utilities, Telecoms)
underperforming as the Fed begins rate hikes. This macro set-up bodes well for a base case continuation of low realized
correlation next year, to the benefit of this trade.
That said, we expect a moderate uptick in volatility next year and assess that the current low liquidity environment presents
an elevated risk of a correlation spike (which may be in part driving the current large correlation premium). As a result, we
recommend trading S&P 500 dispersion with equal vega notionals on the index and single stock legs (known as a ‘vanilla
dispersion trade’) rather than correlation weights. A vanilla dispersion trade is typically net long volatility because for a
given increase in single stock volatilities the index should experience a smaller increase in volatility (unless correlation rises
more rapidly than volatility); however, it uses the correlation premium to subsidize the cost of maintaining this long
volatility exposure. A vanilla dispersion trade (if held to maturity) in effect captures the difference between the realized
volatility spread between the constituents and index, and the implied volatility spread between the constituents and index
(i.e. the trade P/L would be proportional to the difference between the grey line at expiry and blue line at inception in Figure
121). We note the implied vol spread between the constituents and index remains relatively low by historical standards
(despite picking up recently), and lower than the realized spread over the last ~3 years.
Figure 121: The spread between S&P 500 constituent and index
implied volatility remains lower than realized over the last ~3 years
12%
Spread between avg single stock and
index 6M ATM implied vol
6M realized vol spread
10%
8%
10%
7%
9%
6%
8%
5%
7%
4%
6%
6%
4%
2010
Figure 122: S&P 500 index skew has been diverging from skews on
its constituents,
5%
2011
2012
2013
2014
4%
2010
3%
6M Index 90-110% Skew
2%
Avg 6M SS Skew (Right axis)
1%
2011
2012
2013
2014
Furthermore, we note a divergence between S&P 500 index and average constituent skews (Figure 122), which is driving
the correlation skew (i.e. slope of implied correlation by strike) to historic highs. An attractive implementation of the
dispersion trade that takes advantage of this trend is thus to sell 6M S&P 500 index 90% strike straddles vs. buying 6M
90% straddles on its top 50 constituents delta-hedged. 6M 90% straddle implied correlation currently trades at a ~20
correlation point premium to ATM implied correlation ̵ this 90% vs. ATM strike correlation premium is close to cycle
highs, and compares to an average ~14 point premium over the last 4 years.
60
15 December 2014
Marko Kolanovic
(1-212) 272-1438
Euro STOXX 50 dividends: 16s call spread collars
In our base case scenario, we expect the 16s to deliver approximately 9% return in 2015, compared to the 13% expected of
Eurozone equities. Moreover, we argue that the dividend futures present a better risk-reward than equities, due to the lower
growth expectations priced in. Investors can also look to monetize this view via options. The 2016s implied vol is trading at
~45% of the like maturity/strike SX5E vol, still above the pre-October sell off levels (Figure 123), and therefore is an
attractive sell, in our view. We find the payoff profile of call spread collars attractive. Investors can buy 115 - 125
strike call spreads funded by selling 105 puts for a credit of 0.9 points (16s futures ref. 109.5).
Figure 123: 2016/17 dividend implied volatility has not retraced to
pre-sell off levels
Figure 124: Sector break down of the 2016 IBES bottom up estimates
Dividend vol as % of like maturity equity implied vol
Banks
24%
80%
2016s
2017s
70%
60%
50%
Energy
12%
40%
30%
Jun-14
Others
64%
Aug-14
Oct-14
Nov-14
It may be argued that the sector concentration risks in dividends justify a higher risk premium (Figure 124). In particular,
energy names make up 12% of the 2016 estimated SX5E dividends, compared to 8% of the SX5E index. In our view, the
dividend risks on energy names are contained. Our commodity strategists forecast a return to $80+/bbl oil price in 2015,
which enables the energy constituents to maintain their current dividend payout. If the oil price fails to recover, we attach
the highest risk to ENI (JPM 2016e 4.8 index points). The bulk of the SX5E dividends come from TOTAL (JPM 2016e 9.5
index points), which has the balance sheet strength to provide a margin of safety to its dividends.
As we have written before, hedging out the equity risk of dividend futures would generally produce a better risk/return
profile for SX5E dividends. In our view, the case for implementing such a strategy continues to be strong in 2015 as we
expect dividend futures to deliver better returns on a risk-adjusted basis compared to equities.
Figure 125: J.P. Morgan Divimont Index
290
285
280
275
270
Dec-13
Feb-14
Apr-14
Jun-14
Aug-14
Oct-14
61
Marko Kolanovic
(1-212) 272-1438
15 December 2014
Buy short-dated S&P 500 dividend swaps
As discussed in our S&P 500 Dividend Outlook section, US corporate balance sheets remain healthy, which should support
strong dividend growth next year. Cash as % of Total Assets is near a record high (Figure 75), US corporate debt levels are
at multi-decade lows as a % of capitalization (Figure 75), dividend payout ratios are near historical lows (Figure 74), and
our Equity Strategists expect 2015 earnings to grow at an 8% pace. These factors should all support robust dividend growth
in 2015.
2015/16 S&P 500 dividend swaps offer decent upside to bottom-up expectations, and limited risk as they get pulled to
realized next year, in our view. The 2015s currently price in ~6% yoy growth, which we believe is easily achievable given
the strong fundamental set-up. This growth rate is also only around half the realized growth rate dividends recorded in
2014. Bloomberg bottom-up estimates call for ~10% growth next year (a reasonable target in our view, and a ~2.5%
deceleration from 2014’s growth rate), giving ~4% expected upside on this contract. Additionally, given the short time
period until these dividend swaps realize, downside risk is limited in our view.
Similarly, 2016 dividends offer an attractive risk-reward in our view, as they trade at a ~8% discount to bottom-up estimates
(43.5 implied vs. 47.1 points expected according to Bloomberg forecasts) and should get pulled to realized over the course
of next year. The ~4% annualized yield on short-dated S&P 500 dividends compares favorably to other short-dated yield
instruments ̵ for example, the yield to maturity on 3Y High Grade corporate bonds13 is just ~1.8% (Figure 126).
Figure 126: Short-dated S&P 500 dividends compare favorably to
other US yield instruments
5%
4%
Ann. Yield
3%
2%
1%
0%
2Y
3Y HG 2015 SPX 2016 SPX <2Y HY
Treasuries Corporate Dividend Dividend Corporate
Bonds
Swaps
Swaps
Bonds
Source: J.P. Morgan. HG bond yield based on JPM JULI indices, HY bonds based on JPM
Domestic HY bond indices. As of 9-Dec-2014.
We note the Energy sector presents some risk to the 2015/16 dividends, due to the recent fall in Oil prices. Energy
companies are expected to deliver ~12% of total S&P 500 dividends in the next two calendar years, and account for ~25%
of dividend growth. Additionally, this sector’s dividends are relatively concentrated, with 2 names (Exxon and Chevron)
accounting for close to half of the sector total. Continued weakness in Oil prices could reduce these companies’ willingness
to grow their dividends, presenting some downside risk to their forecast dividend growth rates. That said, risks appear
manageable as JPM Integrated Oils analyst Phil Gresh notes Exxon appears well equipped to weather a downturn in oil and
has no need to cut capital plans due to their strong FCF generation, while Chevron has reiterated its commitment to growing
its dividend and is much more likely to cut buybacks than dividends14.
13
Note ~78% of S&P 500 constituents, accounting for ~91% of the index’s weight, are rated Investment Grade (BBB- or better) by
Standard & Poor’s
14
See Exxon Mobil Corp - Good Defense in a Downside Scenario, and Chevron Corp - Cash Conservation Levers Likely Pulled Soon
62
15 December 2014
Marko Kolanovic
(1-212) 272-1438
Monetise the high implied funding spreads for Euro STOXX 50 long-dated TRS
As we discussed in the delta 1 outlook section of this report, the funding spreads implied by Euro STOXX 50 long-dated
delta 1 instruments are currently trading close to its historical highs. This is driven by the demand for long-dated funding
linked to the issuance of Euro STOXX 50 structured products, which tend to leave exotic desks short long-dated index
forwards, combined with reduced ability from banks' delta 1 desks to supply funding, due to the increased capital charges
and balance sheet constraints imposed by the new regulations (e.g. Liquidity Coverage Ratio, Net Stable Funding Ratio).
Investors can take advantage of this market imbalance by selling 5Y TRS on the Euro STOXX 50 at €3M + 82 bps and
buying 1Y TRS on the Euro STOXX 50 at €3M + 53 bps to hedge out delta, dividend and base rate exposure. This
trade earns carry from the difference in funding spreads of the two legs. The main risk when taking the 5Y leg to expiry is
linked to the levels at which it will be possible to roll the short-dated TRS over the life of the transaction.
The trade’s mark-to-market P/L prior to expiry will be driven by the funding carry and by changes in the funding level of
the long-dated TRS, which in turn can be decomposed into a level and a slide component. Should 5Y TRS spreads change,
the impact of the position would be equal to the change in 5Y TRS multiplied by the residual duration of the swap. The risk
for investors is obviously that of a further increase in long-dated funding. Given that the term structure of funding spreads is
strongly upward sloping, as time passes the long-dated TRS leg funding is expected to decline (i.e. slide down). Currently,
the steepness between the 5Y and 4Y part of the funding spread curve is 10bp.
Figure 127: The funding spreads implied by Euro STOXX 50 longdated delta 1 instruments are currently trading close to its historical
highs
Figure 128:The Euro STOXX 50 term structure of funding spreads is
upward sloping; as time passes the implied funding of the short leg
of the trade is expected to decline (positive carry from TS slide)
Euro STOXX 50 5Y and 1Y mid funding spreads (- borrow)
Euro STOXX 50 TRS mid levels
1.0%
1.0%
5Y
0.5%
0.8%
1Y
0.6%
0.0%
0.4%
-0.5%
0.2%
May-14
May-13
May-12
May-11
May-10
May-09
May-08
May-07
May-06
-1.0%
0.0%
1Y
2Y
3Y
4Y
5Y
The 5Y vs. 3M Euro STOXX 50 TRS spread trade that we initiated on the 2nd of July 2013 provides a good illustration on
how this strategy performs from a MTM perspective. The trade was initiated when the 5Y funding spread was at 85bps, not
very far from the current levels, but nevertheless the trade mark-to-market is well in the black with a gain of 130 bps, thanks
to the positive impact of the carry and the slide along the funding curve. The overall P/L contribution of the positive carry
led to a gain of 80 bps since inception, while the cumulative impact of the slide and the curve remarks led to a gain of
50bps, which can be almost entirely attributed to the impact of the slide along the steep TRS curve.
63
Marko Kolanovic
(1-212) 272-1438
15 December 2014
Hedging Trades
Hedge the Japanification of the Eurozone with Euro STOXX 50 long-dated puts
While not our base case, one potential headwind facing the Eurozone is a prolonged period of low inflation/deflation in case
the ECB fails to deliver any substantial measures. In this scenario we believe volatility on the Euro STOXX 50 would be
significantly higher.
As a case study, we look at Japan between 1990 and 2008, when deflation was prevalent, and before the BoJ took
aggressive action. Figure 129 shows the movements in Nikkei in that period (deflation periods shaded in blue, indicated by
negative YoY change in CPI with a 6 month lag). We can also make similar observations on Yen and JGB yields. We find
that the deflationary periods are generally characterised by falling equity prices, strengthening Yen, and low JGB yields.
2Y 80 – 100% skew
6%
SX5E 2Y 80-100 Skew
40000
10000
5000
0
1990 1992 1994 1996 1998 2000 2002 2004 2006 2008
3%
2%
1%
2014
15000
2012
20000
4%
2004
25000
2002
30000
5%
2000
35000
2010
45000
Figure 130: SX5E 2Y 80 – 100 skew at record low
2008
Nikkei 225 index
2006
Figure 129: Nikkei history overlaid with deflation periods (shaded)
Based on our analysis above, we can conclude that if the Euro area stays in the current low inflationary environment for an
extended period of time, we will be faced with significantly higher levels of equity volatility. As mentioned at the beginning
of the report, we assign a relatively low probability to this scenario. However, the recent flattening in the downside skew on
the SX5E index seems to underestimate the potential increase in volatility on the downside (Figure 130), and therefore
provides a good entry point for tail hedge buying.
A 2Y 80% SX5E put option costs indicatively 5.45%. We can also cheapen the hedge by adding conditionalities, in
which case we find better pricing at shorter maturities. Indicatively, a Jun-15 95% put option on SX5E contingent on
EUR > 1.3 costs 2.9%; the same put option on SX5E contingent on 10Y EUR swap yield < 0.8% costs 3.2%
(compared to a vanilla SX5E Jun-15 95% put option cost of 4.9%).
64
15 December 2014
Marko Kolanovic
(1-212) 272-1438
FTSE hedges: Jun-15 knock-in put spreads and FX conditionality
The FTSE could come under pressure in 2015 as general elections in May are unlikely to provide a market friendly result
regardless of the winning party, and lower commodity prices continue to weigh on the commodity-heavy FTSE index. Our
equity strategists remain underweight the UK heading into 2015 and further cite the FTSE's heavy weighting in Defensives
and potential BoE monetary tightening leading to a stronger GBP vs. Euro as likely drivers of underperformance next year.
FTSE skew is one of the steepest globally, and we expect this to persist next year, as demand for hedges persists while the
impact of structured products remains very limited, unlike for other European indices. We recommend investors to take
advantage of the high skew for hedging structures such as put spreads and knock-in put spreads or the low correlation to FX
for puts conditional on GBPUSD.
Cheapen a Jun-15 ATM put by ~30% by selling a 90% put that knocks in at 80%. Investors have the same payout as
an ATM put unless the FTSE is down 20% by June expiry (Figure 131). This represents a fall in the FTSE below the lows
seen at the height of the taper tantrum in the summer of 2012. Should this occur (unlikely in our view) the structure would
still offer the same protection as a vanilla ATM/90% put spread. Indicative price: 3.6% vs. 5.3% for an ATM put outright or
3.4% for a vanilla ATM/90% put spread (FTSE ref. 6529.47).
Figure 131: A FTSE ATM/90% put spread KI at 80% offers the same protection as an ATM put for ~70% of the
price, unless the FTSE falls > 20% by Jun-15 expiry in which case it becomes an ATM/90% put spread
FTSE
6900
Barrier
6700
6500
6300
6100
5900
Full protection
unless the FTSE
falls by 20% by June
5700
5500
5300
5100
Nov-13
Sep-13
Jul-13
May-13
Mar-13
Jan-13
Nov-12
Sep-12
Jul-12
May-12
Jan-12
Mar-12
Nov-11
Sep-11
Jul-11
May-11
Mar-11
Jan-11
4900
Significantly cheapen Jun-15 puts by introducing conditionality on GBPUSD. For example, investors can buy:

Jun-15 6200 put contingent on GBPUSD below 1.53 at expiry at 70ip vs. 205ip for the 6200 put outright

Jun-15 dual digital with the FTSE<=6200 and GBPUSD <1.52 at expiry for 10% (i.e. pay 10 and get 100 if
conditions are met)
GBPUSD has been on a downward trend for most of the year and is likely to continue this in 2015. Our FX strategists
expect 1.50 by mid-year as UK rate expectations prove sticky even as the Fed hikes. They forecast a steadier GBP in 2H as
the BoE hikes with a year-end target of 1.53. We therefore think the discounts offered by making the FTSE puts conditional
on GBPUSD are attractive, especially as a hedge for UK uncertainty in H1 (GBPUSD ref. 1.57, FTSE Dec14 fut ref. 6535).
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15 December 2014
Marko Kolanovic
(1-212) 272-1438
Selling put ratios - taking advantage of cheap volatility and skew
Although China and Japan are both OWs in our country allocation strategy, there are significant risk factors which can
derail the current bullish sentiment and market rally. For China, the risk to manage in 2015 is a decline in Chinese
construction activity and consumption momentum. It is possible that growth slows faster than our cautious view. This could
accelerate the deterioration in asset quality challenging our assumption of socialized risk, which could potentially result in a
sharp sell-off in the equity market. For Japan, the failure to push ahead with the planned increase in consumption tax could
be taken as a sign of a weak government and failure of Abenomics to put an end to deflation, achieve sustainable economic
growth and fiscal stability. The delay in the tax move is a significant development for Japan's credit rating profile, which has
resulted in Moody’s Investors Service cutting Japan’s rating from Aa3 to A1 to reflect the nation’s higher default risk.
Although the bond market remains calm in the aftermath of the downgrade, we should be mindful of the possibility of
additional downgrades in a chain reaction, which can lead to a surge in yields and volatility spikes in the bond and equity
markets. Considering the level of disagreement among the bulls and bears for these two markets, we present below a
hedging strategy which takes advantage of the downside skew flatness in H-shares and Nikkei 225 (see Figure 132).
A short put ratio strategy is deployed by buying multiple far OTM puts financed by selling one OTM put with a higher
strike. See Table 20 for the indicative option pricing. Along with implied volatility, skews have come down across global
equities indices as tail risk diminished with strong policy support and market rally. For H-shares and Nikkei 225, whose 1Y
85%-95% skew spreads are among the lowest versus other global indices despite its relatively higher implied volatility and
also have the lowest percentiles versus their history since 2008, this long skew strategy looks very attractive (see Figure
134). In addition, for H-shares, its 1Y downside skew spread is also at the lowest level relative to its ATM implied volatility
(Figure 133). We prefer this strategy to going long equity volatility outright, as it is less affected by low realized
volatility/negative carry as a spread trade. This strategy can be also a cheap way to hedge against a potential market
correction as the skew spread is likely to expand from the current low levels in such scenarios.
Table 20: Indicative option pricing of short 1Y 1x2 95%-85% put ratios for major global indices
1Y 85%-95% Skew (Current)
%tile since 2008 (Current)
High since 2008
Low since 2008
Short 1Y 1x2 95%-85% Put Ratio Premium
HSCEI
HSI
0.4%
0.0%
3.5%
0.4%
-0.03%
1.0%
0.0%
3.6%
1.0%
-0.80%
NKY KOSPI2
1.2%
10.6%
3.9%
0.8%
0.21%
1.4%
4.0%
3.4%
1.1%
-0.86%
SX5E
AS51
UKX
SPX
2.0%
1.1%
3.9%
1.9%
-0.04%
2.7%
55.6%
3.3%
2.1%
-0.23%
3.1%
55.8%
3.9%
2.5%
-0.07%
3.3%
74.7%
3.9%
2.2%
0.34%
Source: J.P. Morgan Equity Derivatives Strategy. Data as of December 5, 2014. Negative premium means investors will receive the premium.
Figure 132: HSCEI and NKY downside skew trading at lowest levels
since 2008
Figure 133: 1Y 85%-95% downside skew spread versus 1Y ATM
implied volatility for H-shares
1Y 85%-95% downside skew spread
1Y 85%-95% downside skew spread
4.0%
4.0%
3.5%
3.5%
3.0%
3.0%
2.5%
2.5%
2.0%
2.0%
1.5%
1.5%
1.0%
0.5%
0.0%
Jan-08
Jan-09
Jan-10
Jan-11
66
1.0%
HSCEI
NKY
SPX
UKX
0.5%
0.0%
Jan-12
Jan-13
Jan-14
0%
10%
20%
30%
40%
50%
1Y ATM Implied Volatility
60%
70%
80%
15 December 2014
Marko Kolanovic
(1-212) 272-1438
At maturity, this strategy will provide protection against large market corrections if the spot goes below the lower strike
(85%) but may lead to a loss up to 10% if the spot ends between the two strikes (85% - 95%). Therefore this strategy is
suitable for investors who believe that the market is likely to remain in a range bound mode but want to hedge against a
potential tail risk event. Note that in a market crash scenario, investors may benefit from this strategy on a mark-to-market
basis as the strategy is long volatility and long skew (see Figure 134 and Figure 135 for the mark-to-market scenario
analysis of shorting 1Y 1x2 95%-85% put ratios on H-shares).
Figure 134: MTM scenario analysis of short HSCEI 1Y 1x2 95%-85%
put ratios versus spot change
Figure 135: MTM scenario analysis of short HSCEI 1Y 1x2 95%-85%
put versus volatility change
Profit and Loss (Index Points)
Profit and Loss (Index Points)
5000
Current
After 6M
After 1Y
Current Spot
P&L (Index Points)
4000
400
Current
After 3M
After 6M
300
200
3000
100
2000
0
-10
1000
-8
-5
-3
0
3
5
8
10
-100
0
5,000
6,563
8,125
9,688
11,250
Underlying Spot (Index Points)
-1000
12,813
14,375
-200
Volatility Shift (Volatility Points)
-300
67
15 December 2014
Marko Kolanovic
(1-212) 272-1438
Hedging a Japan armageddon scenario with long-dated volatility
As mentioned above, while our strategists are not bearish on Japanese equities, a major risk factor that investors face is the
heightened uncertainty over the achievability of fiscal deficit reduction. The downgrade from Aa3 to A1 by Moody’s
Investors Service follows Prime Minister Shinzo Abe’s decision to delay a planned sales tax hike to 2017 and call a general
election for mid-December. The delay came after Japan, the world’s third largest economy, fell into recession last month as
the economy contracted for the second quarter in a row. According to Moody’s, the rate cut was also due to uncertainty over
the timing and effectiveness of growth enhancing policy measures, against a background of deflationary pressures and
increased risk of rising Japanese government bond yields and reduced debt affordability over the medium term. At over 1
quadrillion yen ($8.34 trillion), Japan has one of the largest sovereign debts among major economies. The government
pledged to halve its primary deficit by fiscal 2015 and achieve a surplus by fiscal 2020, but the delayed tax hike has cast that
goal in doubt.
While Moody's decision to lower Japan's sovereign debt rating had limited impact on the equity market at the time, there is
a remote possibility that this risk factor can escalate in the medium to long term. To hedge against this tail risk efficiently,
investors can consider using forward starting volatility on Nikkei 225 for long dated tenors ranging from three to five years
to take advantage of the downward sloping term structure (see Figure 136). Unlike S&P 500 where demand from insurance
companies hedging guarantees embedded in variable annuity products drives long-dated volatility, the overwhelming supply
of long dated volatility from autocallable issuance with typical maturities of three to five years has resulted in the inverted
term structure for Nikkei 225.
Figure 136: Nikkei 225 and S&P 500 term structures
Figure 137: Nikkei 225 forward volatility and term structure
Implied volatility
Implied volatility
25%
35%
20%
30%
Term structure spread
Nikkei 225 1Y Forward 2Y ATM Implied Volatility (LHS)
Nikkei 225 1Y-3Y ATM Term Structure Spread (RHS)
3%
2%
1%
15%
25%
0%
10%
20%
-1%
Nikkei 225
S&P 500
5%
1M
2M
3M
6M
9M
1Y
2Y
3Y
4Y
5Y
15%
Dec-09
Dec-10
Dec-11
Dec-12
Dec-13
-2%
Dec-14
Owning forward volatility is a useful way to be long volatility without suffering negative carry – a forward volatility
position earns profit and loss from changes in the implied volatility curve and has no direct exposure to realized volatility.
However, forward volatility positions do have exposure to slide, meaning that if the (upward sloping) volatility term
structure is unchanged, a forward volatility position will slide down that curve and lose money. On the other end, a flat or
downward sloping term structure, as in the case for Nikkei 225, means that long forward volatility positions have low
expected slide – making them an attractive way to position for volatility spikes.
In terms of trade implementation, we prefer using forward starting straddles rather than forward starting variance to avoid
paying for the convexity richness. The “sweet” spot on the Nikkei 225 term structure to position for long volatility exposure
is around the 3Y and 4Y buckets (i.e. Dec17 and Dec18 expiries) which coincide with most of the effective duration for the
outstanding autocallable products. For forward volatility, investors can consider pairing up these two buckets versus the 1Y
and 2Y volatilities (i.e. Dec15 and Dec16 expiries). As shown in Figure 137, the 1Y forward 2Y ATM implied volatility is
trading at the low end of its 5Y history, providing an attractive level for long volatility positioning. Indicatively, the
Dec15/Dec17 and Dec15/Dec18 ATM forward straddles can be purchased at 21.59% and 21.66% implied volatilities
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Marko Kolanovic
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15 December 2014
respectively while the Dec16/Dec17 and Dec16/Dec18 ATM forward straddles can be purchased at 21.32% and 21.56%
implied volatilities respectively.
Nikkei 225 long dated volatility skew is also depressed and collapsed into negative territory, a level unseen since the
beginning of Abenomics in 4Q12 (see Figure 138). To monetize the long dated suppressed skew, investors can consider
going long corridor variance swaps. A corridor variance swap differs from a standard variance swap in that only returns
within a range are counted towards the swap payout; all other returns outside the range are taken to be zero. Consequently
the corridor variance swap strike will therefore trade below the equivalent standard variance swap strike.
For instance, a Dec17 50%-110% corridor variance swap can be entered at 25.5%, which is trading at a 2 point discount
compared to the current pricing of the Dec17 standard variance swap at 27.5%. For this corridor variance swap, investors
will have long volatility exposure for the duration when Nikkei 225 is between 50% and 110% of the current spot and have
no exposure for the time spent outside of the corridor. By taking a view on the volatility levels encapsulated in the skew
where it is priced cheaply (i.e. cheap downside volatility relative to rich upside volatility), this instrument enables investors
to buy variance at more attractive levels, contingent on the Nikkei 225 spot level. Hence, this variance swap strategy can be
seen as a way to go long downside volatility at a discount by taking advantage of the flat long dated skew and hedge against
a sharp fall in the equity market for up to 50% below the current spot. This type of market decline would wipe out all the
gains since the start of Abenomics, which is possible should the reform strategies fail. However, this hedging strategy would
not perform well if Nikkei 225 remains in a tight trading range, resulting in low realized volatility.
Figure 138: Nikkei 225 and S&P 500 long dated skew
Figure 139: Nikkei 225 price and volatility versus the corridor levels
90—110% skew
Index level
5%
Volatility
20000
4%
35%
17000
3%
30%
14000
25%
2%
1%
0%
Dec-09
11000
Nikkei 225 3Y 90%-%110 Skew
Nikkei 225 5Y 90%-%110 Skew
S&P 500 3Y 90%-%110 Skew
S&P 500 5Y 90%-%110 Skew
Dec-10
Dec-11
-1%
20%
8000
Dec-12
Dec-13
Nikkei 225 (LHS)
50% Corridor (LHS)
110% Corridor (LHS)
3Y Realized Volatility (RHS)
Dec-14
5000
Dec-04
Dec-06
Dec-08
Dec-10
Dec-12
15%
Dec-14
69
15 December 2014
Marko Kolanovic
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S&P 500 hedging strategy menu
The absence of a meaningful sell-off in markets over the last few years (e.g. the last time the market fell more than 10%
peak-to-trough was more than 3 years ago) means hedging strategies have been generally unnecessary in retrospect. As
such, any comparative analysis of the recent performance of hedging strategies will generally favor strategies that are lower
cost/cheaper to carry. Rather than evaluating the ex-post effectiveness of hedging strategies historically during a period
where they weren‘t needed, in this section we simply examine the cost of initiating new hedges based on their relative cost.
We examine the cost of a range of strategies across various tenors within a historical perspective, as a reference for
investors looking to tactically hedge their US or global equity exposure via S&P 500 protection strategies. This screen can
help investors to identify relatively over/undervalued parts of the volatility surface where they can get the best value for
their hedging budget. Figure 140 below shows the current cost and 2Y cost percentiles for a range of strategies at 3M, 6M
and 1Y tenors (all based on indicative mid prices). Updated pricing on many of these (and similar) structures is available in
our weekly Americas Index Hedging Strategies screen, published on J.P. MorganMarkets.
Figure 140: S&P 500 hedging strategies
Tenor
Strategy
Puts
3M
Cost or
Strike
2Y %ile
6M
Cost or
Strike 2Y %ile
1Y
Cost or
Strike
2Y %ile
ATM Put
2.7%
29%
4.4%
45%
6.8%
42%
95% Put
1.3%
48%
2.7%
56%
4.9%
50%
90% Put
0.6%
61%
1.7%
64%
3.5%
58%
85% Put
0.4%
69%
1.1%
71%
2.5%
66%
80% Put
0.2%
77%
0.7%
75%
1.8%
71%
ATM-90% Put Spread
2.0%
13%
2.7%
13%
3.3%
5%
95-85% Put Spread
0.9%
24%
1.6%
27%
2.4%
16%
90-80% Put Spread
0.4%
46%
1.0%
43%
1.7%
26%
104.0%
85%
104.2%
81%
104.0%
61%
0.5%
32%
0.3%
37%
0.2%
46%
103.1%
46%
104.3%
37%
107.0%
40%
0.8%
18%
0.0%
28%
1.5%
17%
95.4%
37%
92.9%
28%
89.5%
27%
Put Spreads
Collars/Put Spread Collars
90% Put/Cashless Collar
Strike*
95-85-105% Put Spread
Collar (90-80-110% for 1Y)
95-85% Put Spread/
Cashless Collar Strike*
Put Ladders/Ratios
ATM-95-90% Put Ladder
(ATM-90-80% for 1Y)
Costless 1 ATM x2 OTM Put
Ratio Strike
Source: J.P. Morgan Equity Derivatives Strategy. * Expressed as 100%-Percentile, since higher values are preferable. As of 5-Dec-2014.
The relative costs in Figure 140 largely mirror the volatility surface richness shown in the skew section (Figure 37), and
indicate that far OTM puts are relatively expensive and are attractive to sell via put spreads, put ladders and put ratios. Due
to the relatively cheap close-to-the-money call wing vols and expensive OTM put vols, collars generally appear expensive.
70
Marko Kolanovic
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15 December 2014
Additional Basket Methodology
In order to keep the basket relevant to the investment theme, J.P. Morgan reserves the right to review the following at any
time:
• Basket methodology. This is to ensure the rules of the basket remain relevant following any structural changes to the
theme. This may include ensuring that the sector exposure of the basket remains broadly consistent with the investment
theme.
• Basket change implementation. J.P. Morgan will consider extending the implementation of changes to the basket
composition from one trading session to any period up to five trading sessions in the event that a material increase in the
liquidity or capacity of the basket is required to minimize market impact.
Corporate actions may affect the baskets. The composition of a custom basket is typically adjusted in the following manner:
Cash Merger. The divisor is adjusted, and we remove the merging company from the basket on the day of merger and
redistribute gains into remaining companies according to recalculated market cap weights of surviving constituents in the
basket.
Stock Merger. If the acquirer is a member of the basket, then the weight allocated to the acquired will transfer to the
surviving entity on the close of the last day it trades. If the acquirer is not a part of the basket, then proceeds (losses) from
the acquired company will be redistributed to the surviving basket constituents based on the recalculated weighting on the
close of its last trading day.
Spinoffs. The spinoff company and parent will be included in the basket, and both the spinoff and parent company weights
will be readjusted according to new market capitalizations after the spinoff date.
Tender Offers and Share Buybacks. The company remains in the basket and its weight is adjusted according to the impact
the tender/buyback has on the stock’s market value.
Delisting/Insolvency/Bankruptcy. The company is removed from the basket as of the close of the last trading day, and the
proceeds (losses) will be redistributed into remaining companies according to re-calculated weights of remaining companies
in the basket. If a stock trades on “pink sheets” it will not be included in the basket.
Bloomberg subscribers can use the tickers JPDEER15, JPHCHBK2, JPHCHSOE, JPHINLOI, JPAMFINL, JPAMAIRL,
JPAMENRG, JPAMSYLD, JPAMDREV, JPUSTP15, JPUSGP15, JPUSVP15, JPUSIP15, JPUSSP15, JPDECW15,
JPDEDP15, JPDEBB15, JPDEEX15, JPHJTPOT, and JPHKSDV2 to access tracking information on a basket created by the
J.P. Morgan Derivatives desk to leverage the theme discussed in this report. Over time, the performance of JPDEER15,
JPHCHBK2, JPHCHSOE, JPHINLOI, JPAMFINL, JPAMAIRL, JPAMENRG, JPAMSYLD, JPAMDREV, JPUSTP15,
JPUSGP15, JPUSVP15, JPUSIP15, JPUSSP15, JPDECW15, JPDEDP15, JPDEBB15, JPDEEX15, JPHJTPOT, and
JPHKSDV2 could diverge from returns quoted in our research, because of differences in methodology. J.P. Morgan
Research does not provide research coverage of this basket and investors should not expect continuous analysis or
additional reports relating to it. For more information, please contact your J.P. Morgan salesperson or the Derivatives Desk.
71
Marko Kolanovic
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15 December 2014
Possible Risks of Investing in ETFs
The following is an incomplete list of possible risks of investing in ETFs. Not all of the risks will apply to each investment in ETFs and the
applicable risks will depend on the particular ETFs invested in and the particular facts and circumstances and investment objectives of the
individual investor.
Commodities Risk. Certain ETFs invest in commodities. The commodities industries can be significantly affected by the level and volatility
of commodity prices; world events including international monetary and political developments; import controls and worldwide competition;
exploration and production spending; and tax and other government regulations and economic conditions.
Concentration Risk. An ETF may, at various times, concentrate in the securities of a particular industry, group of industries, or sector, and
when a fund is overweighted in an industry, group of industries, or sector, it may be more sensitive to any single economic, business,
political, or regulatory occurrence than a fund that is not overweighted in an industry, group of industries, or sector.
Costs of Investing in Underlying ETFs. Certain ETFs invest in other ETFs, and will bear a pro rata portion of the underlying ETFs’
expenses (including operating costs and management fees).
Credit Risk. An ETF could be subject to the risk that a decline in the credit quality of a portfolio investment could cause the ETF’s share
price to fall. The ETF could lose money if the issuer or guarantor of a portfolio investment or the counterparty to a derivatives contract fails
to make timely principal or interest payments or otherwise honor its obligations.
Early Closing Risk. An unanticipated early closing of the exchange on which an ETF’s shares trade may result in a shareholder’s inability
to buy or sell shares of the ETF on that day.
Emerging Markets Risk. There is an increased risk of price volatility associated with an ETF’s investments in emerging market countries,
which may be magnified by currency fluctuations relative to the U.S. dollar.
Equity Risk. The prices of equity securities in which an ETF may invest rise and fall daily. These price movements may result from factors
affecting individual companies, industries or the securities market as a whole.
Fixed Income Risk. An ETF’s investments in fixed income securities are subject to the risk that the securities may be paid off earlier or later
than expected. Either situation could cause the ETF to hold securities paying lower-than-market rates of interest, which could hurt the ETF’s
yield or share price.
Foreign Currency Risk. Currency movements may negatively impact the value of an ETF’s underlying securities, even when there is no
change in the value of the security in the issuer’s home country.
Foreign Securities Risk. An ETF’s investments in securities of foreign issuers involve certain risks including, but not limited to, risks of
adverse changes in foreign economic, political, regulatory and other conditions, or changes in currency exchange rates or exchange control
regulations (including limitations on currency movements and exchanges). In certain countries, legal remedies available to investors may be
more limited than those available with respect to investments in the United States. In addition, the securities of some foreign companies
may be less liquid and, at times, more volatile than securities of comparable U.S. companies.
High Yield Risk. Certain ETFs may invest in high yield securities and unrated securities of similar credit quality (commonly known as “junk
bonds”). High yield securities generally pay higher yields (greater income) than investment in higher-quality securities; however, high yield
securities and junk bonds may be subject to greater levels of interest rate, credit and liquidity risk than funds that do not invest in such
securities, and are considered predominantly speculative with respect to an issuer’s continuing ability to make principal and interest
payments.
Income Risk. An ETF may derive dividend and interest income from certain of its investments. This income can vary widely over the short
and long term. If prevailing market interest rates drop, distribution rates of an ETF’s income-producing investments may decline, which then
may adversely affect the ETF’s value.
Interest Rate Risk. An ETF’s investments in fixed income securities are subject to the risk that interest rates rise and fall over time.
Investment Risk. An investment in an ETF is not a bank deposit and is not insured or guaranteed by the Federal Deposit Insurance
Corporation or any other government agency.
Jurisdiction. US-listed ETFs may not be marketed to foreign investors in certain jurisdictions, and vice versa.
Liquidity Risk. The market for certain investments may become illiquid under adverse or volatile market or economic conditions, making
those investments difficult to sell. The market price of certain investments may fall dramatically if there is no liquid trading market. The lack
of liquidity in an ETF can result in its value being more volatile than its underlying portfolio securities.
Loss of Money. Loss of money is a risk of investing in an ETF.
Market Risk. Due to market conditions, an ETF’s investments may fluctuate significantly from day to day. This volatility may cause the value
of your investment in the Fund to decrease.
Strategy Risk. ETFs use different strategies, all of which are associated with different risks. For example, an equities-based ETF may use a
large-capitalization, mid-capitalization, small-capitalization or other type of strategy.
Tracking Error Risk. Although many ETFs may seek to match the returns of an index, an ETF’s return may not match or achieve a high
degree of correlation with the return of its applicable index.
Trading Risks. An ETF faces numerous market trading risks, including the potential lack of an active market for its shares, losses from
trading in secondary markets, and disruption in the creation/redemption process of the ETF. Any of these factors may lead to the ETF’s
shares trading at a premium or discount to net asset value (“NAV”), which may be material. In certain markets, ETF prices have dropped
precipitously and experienced greater volatility than prices of other stocks.
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Marko Kolanovic
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15 December 2014
Risks of Common Option Strategies
Risks to Strategies: Not all option strategies are suitable for investors; certain strategies may expose investors to significant
potential losses. We have summarized the risks of selected derivative strategies. For additional risk information, please call
your sales representative for a copy of “Characteristics and Risks of Standardized Options.” We advise investors to consult
their tax advisors and legal counsel about the tax implications of these strategies. Please also refer to option risk disclosure
documents.
Put Sale. Investors who sell put options will own the underlying stock if the stock price falls below the strike price of the
put option. Investors, therefore, will be exposed to any decline in the stock price below the strike potentially to zero, and
they will not participate in any stock appreciation if the option expires unexercised.
Call Sale. Investors who sell uncovered call options have exposure on the upside that is theoretically unlimited.
Call Overwrite or Buywrite. Investors who sell call options against a long position in the underlying stock give up any
appreciation in the stock price above the strike price of the call option, and they remain exposed to the downside of the
underlying stock in the return for the receipt of the option premium.
Booster. In a sell-off, the maximum realised downside potential of a double-up booster is the net premium paid. In a rally,
option losses are potentially unlimited as the investor is net short a call. When overlaid onto a long stock position, upside
losses are capped (as for a covered call), but downside losses are not.
Collar. Locks in the amount that can be realized at maturity to a range defined by the put and call strike. If the collar is not
costless, investors risk losing 100% of the premium paid. Since investors are selling a call option, they give up any stock
appreciation above the strike price of the call option.
Call Purchase. Options are a decaying asset, and investors risk losing 100% of the premium paid if the stock is below the
strike price of the call option.
Put Purchase. Options are a decaying asset, and investors risk losing 100% of the premium paid if the stock is above the
strike price of the put option.
Straddle or Strangle. The seller of a straddle or strangle is exposed to stock increases above the call strike and stock price
declines below the put strike. Since exposure on the upside is theoretically unlimited, investors who also own the stock
would have limited losses should the stock rally. Covered writers are exposed to declines in the long stock position as well
as any additional shares put to them should the stock decline below the strike price of the put option. Having sold a covered
call option, the investor gives up all appreciation in the stock above the strike price of the call option.
Put Spread. The buyer of a put spread risks losing 100% of the premium paid. The buyer of higher ratio put spread has
unlimited downside below the lower strike (down to zero), dependent on the number of lower struck puts sold. The
maximum gain is limited to the spread between the two put strikes, when the underlying is at the lower strike. Investors who
own the underlying stock will have downside protection between the higher strike put and the lower strike put. However,
should the stock price fall below the strike price of the lower strike put, investors regain exposure to the underlying stock,
and this exposure is multiplied by the number of puts sold.
Call Spread. The buyer risks losing 100% of the premium paid. The gain is limited to the spread between the two strike
prices. The seller of a call spread risks losing an amount equal to the spread between the two call strikes less the net
premium received. By selling a covered call spread, the investor remains exposed to the downside of the stock and gives up
the spread between the two call strikes should the stock rally.
Butterfly Spread. A butterfly spread consists of two spreads established simultaneously. One a bull spread and the other a
bear spread. The resulting position is neutral, that is, the investor will profit if the underlying is stable. Butterfly spreads are
established at a net debit. The maximum profit will occur at the middle strike price, the maximum loss is the net debit.
Pricing Is Illustrative Only: Prices quoted in the above trade ideas are our estimate of current market levels, and are not
indicative trading levels.
73
Marko Kolanovic
(1-212) 272-1438
15 December 2014
Disclosures
This report is a product of the research department's Global Equity Derivatives and Quantitative Strategy group. Views expressed may
differ from the views of the research analysts covering stocks or sectors mentioned in this report. Structured securities, options, futures
and other derivatives are complex instruments, may involve a high degree of risk, and may be appropriate investments only for
sophisticated investors who are capable of understanding and assuming the risks involved. Because of the importance of tax
considerations to many option transactions, the investor considering options should consult with his/her tax advisor as to how taxes affect
the outcome of contemplated option transactions.
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analysts are primarily responsible for this report, the research analyst denoted by an “AC” on the cover or within the document
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expressed in this report accurately reflect his or her personal views about any and all of the subject securities or issuers; and (2) no part of
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Important Disclosures
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J.P. Morgan Equity Research Ratings Distribution, as of September 30, 2014
J.P. Morgan Global Equity Research Coverage
IB clients*
JPMS Equity Research Coverage
IB clients*
Overweight
(buy)
46%
57%
46%
76%
Neutral
(hold)
42%
49%
48%
67%
Underweight
(sell)
12%
34%
7%
51%
*Percentage of investment banking clients in each rating category.
For purposes only of FINRA/NYSE ratings distribution rules, our Overweight rating falls into a buy rating category; our Neutral rating falls into a hold
rating category; and our Underweight rating falls into a sell rating category. Please note that stocks with an NR designation are not included in the table
above.
74
Marko Kolanovic
(1-212) 272-1438
15 December 2014
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(1-212) 272-1438
15 December 2014
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Copyright 2014 JPMorgan Chase & Co. All rights reserved. This report or any portion hereof may not be reprinted, sold or
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2015 Equity Derivatives Outlook

Transcription

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