2015 Equity Derivatives Outlook - Catley...

www.jpmorganmarkets.com

Global Quantitative and Derivatives Strategy15 December 2014

2015 Equity Derivatives OutlookVolatility Forecasts and Trade Ideas

Global Quantitative and Derivatives Strategy

Marko Kolanovic AC

(1-212) 272-1438

[email protected]

J.P. Morgan Securities LLC

Davide Silvestrini AC

(44-20) 7134-4082

[email protected]

J.P. Morgan Securities plc

Tony SK Lee AC

(852) 2800-8857

[email protected]

J.P. Morgan Securities (Asia Pacific) Limited/ J.P. Morgan Broking (Hong Kong) Limited

Bram Kaplan, CFA AC

(1-212) 272-1215

[email protected]

J.P. Morgan Securities LLC

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.

Equity Derivatives & Delta-One Strategy Team

US

Marko Kolanovic [email protected]

Bram Kaplan [email protected]

AJ Mehra [email protected]

Min Moon [email protected]

EMEA

Davide Silvestrini [email protected]

Peng Cheng [email protected]

Anders Armelius [email protected]

Sahil Manocha [email protected]

Rahil Iqbal [email protected]

Asia Pacific

Tony Lee [email protected]

Sue Lee [email protected]

Haoshun Liu [email protected]

Michiro Naito [email protected]

Zhen Wei [email protected]

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Marko Kolanovic(1-212) [email protected]

ContentsEquity 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)

Source: J.P. Morgan Equity Derivatives Strategy.

Table 1: Asset volatility in 2014 - 15-year context


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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Commodity

AverageEquityCreditFXRates

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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%

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Figure 2: S&P 500 1M realized volatility and the VIX


Figure 3: S&P 500 pattern around October selloff


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


More difficult to estimate is the extent to which low current levels of volatility are already anticipating an improvement inmacro 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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Global GDP (FY) 3.00% 3.40% 0.40%

US GDP (FY) 2.30% 3.00% 0.70%

Euro Area GDP (FY) 0.90% 1.60% 0.70%

US Unemployment 5.80% 5.40% -0.40%

US 2002 2250 12.4%

Europe 1342 1550 15.5%

Asia ex-Japan 461 525 14.0%

Japan 1400 1700 21.5%

IG Credit (bps) 72 60 -12

HY Credit (bps) 392 320 -72

Fed Funds Rate 0.13% 1.00% 0.88%

DM CB Rates 0.26% 0.68% 0.42%

EM CB Rates 6.15% 6.09% -0.06%

3M USD LIBOR 0.24% 1.05% 0.81%

US 3Y Treasury Yield 0.97% 2.00% 1.03%

US 10Y Treasury Yield 2.08% 2.80% 0.72%

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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


1 Equity Volatility risk premia is the compensation an investor receives for being short equity risk via a derivative product. 2 For more details see our report VIX Risk Premia and Volatility Trading Signals.

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https://jpmm.com/research/content/GPS-1397469-0

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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).

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

Strategy information ratios 2011 2012 2013 2014 YTD*Max draw

down in 2014

Delta hedged 1M ATM straddles

S&P500 0.88 1.54 -0.03 -0.14 -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%

Outright 1M ATM straddles

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%

Short 30d Var swaps*

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%

Nikkei -0.25 1.95 -0.59 -0.05 -11.3%

Average -0.08 2.73 0.66 0.44 -8.4%

Short VIX/V2X futures**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.

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Figure 8: Hedge Fund leverage and Mutual Fund / ETF flows


Figure 9: NYSE margin debt and US household equity holdings


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


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


Figure 13: Average stock volatility and correlation for each of 10 S&P 500 sectors


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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Average Stock Correlation

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S&P 500 Sector

%-tile Level %-tile Level

C. Discretionary 11 22.9% 47 31.5%

C. Staples 3 16.5% 53 32.1%

Energy 17 21.4% 39 48.9%

Financials 0 17.4% 68 52.0%

Health Care 24 22.6% 77 37.1%

Industrials 2 18.2% 79 52.1%

Technology 1 23.4% 16 30.5%

Materials 2 21.0% 35 38.7%

Telecomms 0 17.6% 60 50.0%

Util ities 17 16.4% 76 62.7%

Average 2 20.4% 62 43.6%

Stock Volatility Correlation

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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 2014VSTOXX less VIX average intraday spread

Source: J.P. Morgan Equity Derivatives Strategy. As of 12-Dec-14

Figure 15: Average absolute quarterly move versus quarterly realized volatility over past 10 years

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, therisk 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


Table 3: …while all global index term structures are upward sloping, apart from NKY

12M-3M ATM Vol Spread

Current 3Y %ileYTD

Average2013

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 front-end 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

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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/OctS&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


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

12%

16%

20%

24%

28%

32%

0 12 24 36 48 60 72 84 96 108 120

maturity (months)

2014 YTD Avg

2013 Avg

2012 Avg

5-Dec-1420%

25%

30%

35%

Jan-12 Jul-12 Jan-13 Jul-13 Jan-14 Jul-14

5Y Variance

12



Figure 19: VIX futures’ carry cost continued to decline in 2014VXX Level (Logarithmic scale)


Figure 20: The effective VIX ETN exposure was negative most of 2014, and reached a record short in the Oct market sell-offUSD Mn


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 correction1Y – 3M ATM Implied Vol Spread (both axis)

Source: J.P. Morgan Equity Derivatives Strategy

Figure 22: Longer-dated vol declined on average over the year across major European indices Volatility points


20

200


VXXSlope (2012)Slope (2013)Slope (2014)

~60bps/day

carry cost

~33bps/day

carry cost~23bps/day

carry cost

-2000

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0

1000

2000

3000

4000

2009 2010 2011 2012 2013 2014

Exposure-weighted AUM in VIX Short-Term ETPs net of Short Interest

-5%

-4%

-3%

-2%

-1%

0%

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0.5%

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2.5%

UK

X

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5E

DA

X

SM

I

IBE

X

FT

SE

MIB

SX

7E

Avg. 2014 1Y-3M ATM vol spread prior to Oct correction

Oct inversion (RHS)

-4%

-3%

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SX

7E

IBE

X

CA

C

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5E

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X

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X

SM

I

Decline in avg. 3Y ATM vol 2014YTD vs. 2013

13



Average long-dated implied volatilities declined across all major European indices compared to last year, reaching multi-year 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 view3Y ATM Implied Vol


Figure 24: Spanish longer-dated vols declined more than Italian ones in 2014

3Y ATM Vol (Vol points)


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 viewBoth axis: Curve steepness for front 6 contracts (vol point per month)

Source: J.P. Morgan Equity Derivatives Strategy. As of 9-Dec-2014.

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)

Number of days where TS was invertedSource: J.P. Morgan Equity Derivatives Strategy

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

14%

19%

24%

29%

34%

De

c-0

9

Apr

-10

Au

g-1

0

De

c-1

0

Apr

-11

Au

g-1

1

De

c-1

1

Apr

-12

Au

g-1

2

De

c-1

2

Apr

-13

Au

g-1

3

De

c-1

3

Apr

-14

Au

g-1

4

De

c-1

4

SX5E UKX DAX

0.18

0.19

0.2

0.21

0.22

0.23

0.24

0.25

0.26

Jan-

13

Mar

-13

May

-13

Jul-1

3

Sep

-13

Nov

-13

Jan-

14

Mar

-14

May

-14

Jul-1

4

Sep

-14

Nov

-14

FTSEMIB IBEX

-0.4

-0.2

0

0.2

0.4

0.6

0.8

1

1.2

1.4

-1.5

-1

-0.5

0

0.5

1

1.5

Jan

-13

Ma

y-1

3

Se

p-13

Jan

-14

Ma

y-1

4

Se

p-14

VIX less V2X (RHS) VIX V2X -10%

-9%

-8%

-7%

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-5%

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0 20 40 60 80 100 120 140

2014

2013 2012

2010

2011

14



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 225Volatility spread Index

Source: J.P. Morgan Equity Derivatives Strategy, “Measuring Economic Policy Uncertainty” by

Scott Baker, Nicholas Bloom and Steven J. Davis at www.PolicyUncertainty.com

Figure 28: H-shares term structure reflects relative revisions between 2014 and 2015 China GDP forecastsVolatility spread %

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.

30

50

70

90

110

130

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210

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Jan-13 Apr-13 Jul-13 Oct-13 Jan-14 Apr-14 Jul-14 Oct-14

NKY 3M-12M IV Spread Japan Economic Policy Uncertainty Index (R)

-0.08

-0.06

-0.04

-0.02

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Nov-13 Feb-14 May-14 Aug-14 Nov-14

HSCEI 3M-12M IV Spread

China GDP Consensus 4W Relative Change: 2014 - 2015 (Inverted, R)

15



Figure 29: Retail structured products issuance recorded a historical high in Korea but slowed down in Japan. Notional (JPY bn) Notional (KRW tn)

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.

Table 4: Short long-dated volatility outright or via calendar spreadsperformed well in Asia ex Japan due to low realized volatility and upward sloping term structure

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) Index Level

Source: J.P. Morgan, Bloomberg.

Figure 31: Nikkei volatility futures open interest and roll costAUM (USD Mn) % Roll cost

Source: J.P. Morgan, Bloomberg. *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 beworth investors' attention.

NKY HSCEI SX5E UKX SPX AS51 KOSPI2 HSI

Curr 2Y Vswap (1) 27.3% 29.1% 23.1% 19.6% 20.8% 19.9% 21.6% 24.0%

Curr 1Y Vswap (2) 27.4% 27.9% 21.6% 18.1% 19.1% 18.2% 19.6% 21.9%

Curr 1Y-2Y Fwd Vswap (3) 27.1% 30.3% 24.5% 21.0% 22.4% 21.4% 23.4% 26.0%

Spread (1)-(2) -0.1% 1.2% 1.5% 1.5% 1.7% 1.7% 2.0% 2.1%

Spread 10Y Percentile 22% 65% 87% 72% 81% 66% 87% 82%

PnL of Short 1Y Varswap over past 1 year

Average 0.5% 5.4% 5.5% 5.4% 6.0% 4.7% 6.1% 5.2%

Min -7.2% 2.3% 3.0% 3.1% 4.7% 2.2% 3.9% 2.7%

Max 7.2% 9.0% 7.8% 7.4% 8.3% 7.4% 7.7% 8.2%

PnL of Short 1Y-2Y Forward Variance Swap over past 1 year

Average -0.2% 2.0% 2.6% 2.9% 2.8% 3.5% 3.1% 2.1%

Min -5.9% -2.4% -1.4% -0.9% -2.8% 0.2% 0.0% -1.5%

Max 5.8% 6.3% 6.1% 4.6% 5.9% 5.9% 5.2% 5.5%

16



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 H-shares. 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.

17



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 20146M 90%-110% skew


Table 5: Summary of 6M skews across the globe – sorted by current 6M 90%-110% skew spread

Source: J.P. Morgan Equity Derivatives Strategy. * 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 all-time highs this summer...


Figure 34: … driving S&P 500 levered risk reversals to record leverage levels


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

6M 90-110%

Skew Current

5Y

%i l 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%

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3M 90-110 Skew/ATM Vol

6M 90-110 Skew/ATM Vol

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SPX 6M 90-110% Risk Reversal Leverage Ratio

18



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 outstandingS&P 500 Level Put/Call Open Interest Ratio


Figure 36: Average call moneyness is little changed this cycle vs. last, but puts are struck on average ~7% further OTMOpen interest weighted average moneyness for S&P 500 options


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)


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2004 2006 2008 2010 2012 2014

Avg Call MoneynessAvg Put Moneyness

Tenor 70 75 80 85 90 95 100 105 110 115 120 125 130

1M 0.64 0.53 0.32 0.14 0.36 0.66 0.70

2M 0.67 0.58 0.45 0.28 0.36 0.47 0.48

3M 0.78 0.70 0.62 0.50 0.32 0.37 0.48 0.51 0.51

6M 0.80 0.76 0.71 0.66 0.58 0.51 0.47 0.46 0.54 0.55 0.55

1Y 0.76 0.74 0.72 0.67 0.61 0.55 0.47 0.44 0.42 0.38 0.36 0.36 0.37

2Y 0.77 0.76 0.75 0.72 0.69 0.66 0.62 0.55 0.50 0.45 0.40 0.35 0.31

Strike

19



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 flatterVolatility points


Figure 39: Euro STOXX 50 longer-dated skew has reached historical lows and is looking cheap, in our view2Y 90-110% skew (vol points


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).

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Change in avg. 3M 90-110 Skew 2014-2013

Change in avg. 2Y 90-110 Skew 2014-2013

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UKX SPX SX5E

20



Figure 40: SX5E Skew and dividend term structure de-coupled after the October sell-offStandardized skew Dividend Term Structure


Figure 41: Comparison between SX5E implied skew and 6M put spread max payoff to cost ratioImplied skewness of return distribution Max Payoff/Cost Ratio (times)


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

Index6M 95/105% skew

standardized by ATM volSkew percentile

(since 2005)SPX Index 28.3% 92.4%UKX Index 25.5% 84.9%SMI Index 22.7% 92.4%AEX Index 19.1% 74.6%OMX Index 19.1% 90.4%DAX Index 16.1% 40.8%CAC Index 15.5% 44.8%TOP40 Index 15.3% 45.2%SX5E Index 13.8% 30.2%EEM UP Equity 13.5% 82.7%IBEX Index 10.6% 20.2%XU030 Index 8.4% 56.3%FTSEMIB Index 8.0% 1.0%WIG20 Index 7.4% 29.7%RDXUSD Index 7.1% 36.4%NKY Index 3.8% 23.1%HSI Index 0.9% 0.0%HSCEI Index -2.0% 0.3%


Figure 42: Call away ratio is correlated with implied skewCall away ratio

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).

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Asia: Asian index skews remained largely suppressed, decoupling from other regions. While active structured productissuance (Figure 29) continued to suppress downside volatility8, 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 ConnectVega issuance (USD mn) 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.

Figure 44: Strong demand for China exposure was shown in increased flows in China related derivatives and a pronounced H-shares smileAsset under management (USD Bn) 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.

8Structured 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.



22



Figure 45: Structured product aggregate vega outstanding estimates for Nikkei 225, KOSPI 200 and HSCEI Vega (USD mn)

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.

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 range12M correlation between 12M ATM vol moves (ex-skew) and spot moves


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 doubled 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 actionsNikkei 225 volatility USDJPY volatility


Figure 48: Correlation between H-shares put implied volatility and USDCNY call implied volatility weakened after fx trading band wideningHSCEI volatility USDCNY volatility


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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


Figure 50: The term structure of correlation steepened significantly this year, particularly out to ~1Y tenorS&P 500 implied correlation spread


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 thecorrelation 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.

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Figure 51: European implied and realized correlations reached 2013 highs in the October correction and remain elevated heading into 2015Avg implied and realised correlation across European indices*

Source: J.P. Morgan Equity Derivatives Strategy. * Euro STOXX 50, FTSE, DAX and SMI. As of

12-Dec-2014.

Figure 52: Euro STOXX 50 1M realised correlation hit its YTD lows in the Q2 earnings season and has followed 6M realised higher sinceCorrelation


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 in 2014YTD outperformance


Figure 54: European sector performance has been mixed YTD


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

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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 spreadhas 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 high6M realized correlation


Figure 56: Returns on index-weighted 6M dispersion for ASX 200 suppressed by low levels of volatilityCorrelation spread Dispersion P&L (volatility points)


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).

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Figure 57: Bullish positioning through Hang Seng futures ahead of Shanghai-Hong Kong Stock Connect drove correlation higher3M realized correlation Hang Seng futures open interest


Figure 58: US dollar strength and expectation of further BoJ easing drove USDJPY and TOPIX Core 30 correlation higher3M correlation USDJPY


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 onASX 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.

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Implied Dividends

Euro STOXX 50 DividendsPerformance 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% YTD return

Source: J.P. Morgan, Bloomberg, Return of dividend futures include 1Y Euribor swap yield. As

of 12-Dec-14

Table 7: Historical returns of SX5E dividend futures and related asset classes

YTD 2013 2012 2011JPM Euro BB 7.2% 8.4% 20.1% 5.2%JPM Euro B 4.0% 12.6% 28.7% -1.5%JPM Euro CCC 4.1% 15.4% 37.4% -9.4%DEDZ +1Y 2.4% 10.3% 14.9% -3.3%DEDZ +2Y 1.4% 13.4% 15.7% -14.0%DEDZ +5Y -3.7% 12.4% 18.3% -22.0%SX5T 1.6% 21.5% 18.1% -14.1%

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’sbalance 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 bottomingIndex dividend level


Figure 61: SX5E DPS growth estimates are modest compared to EPSYoY growth rate

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

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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


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 7has 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.

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FTSE 100 DividendsFTSE 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


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 Upside to bottom-up FTSE 100 dividend estimates


A combination of declining implied dividend levels and a weakening of the British Pound relative to the US Dollar in H2-14 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 Upside to JPM and IBES estimates for 2016 FTSE dividend futures


Figure 67: Approximately 29% of FTSE dividends (ip for 2016) are expected to be paid by Energy and Materials companies


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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 DividendsFollowing 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 Ratio Ratio

Source: J.P. Morgan, Bloomberg

Figure 69: Nikkei market implied dividend payout ratio is below the median payout ratio since 2001Ratio Index Points

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

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Trailing 12M Div (R)

31



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 analysisshows 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

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 dividendsIn 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

Nikkei 225 Dividend 2014 2015 2016 2017 2018 2019

Current price 262.0 290.3 315.5 333.8 345.5 352.8

Implied y/y growth 15.9% 10.8% 8.7% 5.8% 3.5% 2.1%

1Y correlation with NKY 60.6% 85.6% 92.4% 92.7% 93.0%

Top-down forecast 300.0 330.0 341.2 352.8 364.8

Bottom-up forecast 279.5 307.8 318.2 329.0 340.2

Upside from current price

Top-down forecast 3.4% 4.6% 2.2% 2.1% 3.4%

Bottom-up forecast -3.7% -2.5% -4.7% -4.8% -3.5%

Ratio of upside to volaitlity

90D price volaitlity 5.2 9.3 11.5 13.0 14.4

Top-down forecast 0.6% 0.5% 0.2% 0.2% 0.2%

Bottom-up forecast -0.7% -0.3% -0.4% -0.4% -0.2%

52wk high 291.8 318.8 338.3 350.0 358.0

52wk high date 29-Jul-14 7-Dec-14 7-Dec-14 8-Dec-14 8-Dec-14

52wk low 260.0 279.8 287.3 291.3 293.8

52wk low date 4-Feb-14 15-Apr-14 19-May-14 19-May-14 19-May-14



32



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 dividendsattractive 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 and Hang Seng in 2014


Figure 72: Bottom-up estimates and marker prices for H-shares and Hang Seng dividends

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 DividendsS&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.

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Staples Contribution to total dividend index points by sector

HSCEI HSI

HSCEI Dividend 2014 2015 2016 2017 2018

Current price 435.4 461.0 464.1 466.0 473.0

Implied y/y growth 5.9% 0.7% 0.4% 1.5%


Implied y/y growth 8.1% 9.7% 8.7% 8.7%

Upside to target 2.1% 11.2% 20.4% 29.0%

HSI Dividend 2014 2015 2016 2017 2018

Current price 908.5 851.5 848.6 846.3 843.2

Implied y/y growth -6.3% -0.3% -0.3% -0.4%


Implied y/y growth -6.6% 7.4% 5.6% 5.6%

Upside to target -0.4% 7.4% 13.7% 20.5%



33



Figure 73: S&P 500 dividends underperformed this year, with a muted beta to the cash index


Figure 74: S&P 500 dividend payout ratio is near historical lows

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...

Source: J.P. Morgan, Factset.

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

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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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.

Figure 77: The S&P 500 dividend curve flattened significantly this year as long-dated dividend swaps underperformed


Figure 78: S&P 500 realized (blue) and implied (grey) annual dividend growth rates


9 See Exxon Mobil Corp - Good Defense in a Downside Scenario, and Chevron Corp - Cash Conservation Levers Likely Pulled Soon

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35



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 theircash 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 year-end similar to 2012 and 20133M 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)


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).

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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.

36



Figure 81: Long-dated funding spreads remained close to historical highs for some indices, particularly the Euro STOXX 505Y implied funding rates


Figure 82: Nikkei 225 implied funding ratesImplied Funding Rate (%)

Source: J.P. Morgan.

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 83and 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.

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Figure 83: Relative performance of collateralized futures vs. gross TR cash – Developed Market indicesPerformance difference of Gross TR cash vs. collateralized futures

(all series rebased to 100 on Jan-07)


Figure 84: Relative performance of collateralized futures vs. gross TR cash – Asian indicesPerformance difference of Gross TR cash vs. collateralized futures

(all series rebased to 100 on Jan-07)


So what can investors do to optimize their investment in the new higher funding environment? Moving to fully fundedinvestments (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 smallcap 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).

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38



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 severalimprovements 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


Figure 86: Euro-zone equity indices skews are flat relative to their histories and relative to most other DM indices

1Y 100-120% Skew 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 3400-3800call 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.

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Euro STOXX 50 SX7E

FTSEMIB IBEX



39



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 (seeEquity 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 withsignificant 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 Sector Country W. European Exposure Basket Weight

CABK SM FINANCIALS SPAIN 100% 2.8%G IM FINANCIALS ITALY 100% 2.8%

ATL IM INDUSTRIALS ITALY 100% 2.8%MS IM DISCRETIONARY ITALY 100% 2.8%

AGS BB FINANCIALS BELGIUM 95% 2.8%INGA NA FINANCIALS NETHERLANDS 93% 2.8%GLE FP FINANCIALS FRANCE 84% 2.8%DG FP INDUSTRIALS FRANCE 82% 2.8%

ENEL IM UTILITIES ITALY 82% 2.8%AC FP DISCRETIONARY FRANCE 76% 2.8%

HMB SS DISCRETIONARY SWEDEN 72% 2.8%SEV FP UTILITIES FRANCE 71% 2.8%UCG IM FINANCIALS ITALY 70% 2.8%CA FP STAPLES FRANCE 69% 2.8%

RAND NA INDUSTRIALS NETHERLANDS 69% 2.8%RNO FP DISCRETIONARY FRANCE 69% 2.8%TIT IM TELECOMS ITALY 69% 2.8%

ALV GR FINANCIALS GERMANY 69% 2.8%MEO GR STAPLES GERMANY 69% 2.8%SGO FP INDUSTRIALS FRANCE 67% 2.8%EZJ LN INDUSTRIALS BRITAIN 66% 2.8%UG FP DISCRETIONARY FRANCE 66% 2.8%CAP FP IT FRANCE 66% 2.8%PRY IM INDUSTRIALS ITALY 63% 2.8%

DPW GR INDUSTRIALS GERMANY 63% 2.8%REP SM ENERGY SPAIN 63% 2.8%

ADEN VX INDUSTRIALS SWITZERLAND 62% 2.8%BOSS GR DISCRETIONARY GERMANY 60% 2.8%TKA GR MATERIALS GERMANY 59% 2.8%AGL IM DISCRETIONARY ITALY 57% 2.8%TOD IM DISCRETIONARY ITALY 55% 2.8%SIE GR INDUSTRIALS GERMANY 53% 2.8%AGN NA FINANCIALS NETHERLANDS 50% 2.8%IFX GR IT GERMANY 41% 2.8%LR FP INDUSTRIALS FRANCE 35% 2.8%

HEI GR MATERIALS GERMANY 30% 2.8%



40



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 historyVolatility spread Index


Figure 88: Correlation between spot and volatility moves remained largely positive for Nikkei 225Correlation


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

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NKY 12M correlation between 12 ATM vol moves (ex-skew) and spot moves

41



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 historicalcontext. 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%


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)

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Dec-94 Dec-98 Dec-02 Dec-06 Dec-10 Dec-14NKY-USDJPY 1Y Weekly Correlation

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Dec-94 Dec-98 Dec-02 Dec-06 Dec-10 Dec-14NKY-JYSW10 1Y Weekly Correlation

42



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.% Thousand

Source: J.P. Morgan Equity Derivatives Strategy, CSDC

Figure 92: Onshore margin trading balance hits 6.8% free float market cap of China A-shares (SHSE +SZSE)% Index

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 A-share 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.

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0%

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15%

20%

25%

Dec-09 Dec-10 Dec-11 Dec-12 Dec-13 Dec-14A-shares % Active Accounts New A-shares Accounts (R)

1,500

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3,000

3,500

4,000

0%

1%

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Apr-10 Apr-11 Apr-12 Apr-13 Apr-14Margin Trading Balance / Free Float Market Cap (SHSE+SZSE)

CSI 300 (R)

43



Table 9: Indicative options pricing of on H-shares and FTSE China A50

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)


Figure 94: China Bank Basket <JPHCHBK2> composition

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 95: China SOE Reform Beneficiaries <JPHCHSOE> composition

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

Figure 96: Indicative pricing of bullish strategies for JPHCHSOE and JPHCHBK2.


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%

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Dec-13 Apr-14 Aug-14 Dec-14

JPHCHBK2 JPHCHSOE MXCNTicker 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

Ticker Name Curr Mkt Cap Avg T/O Index

Price ($mn) ($mn) Wgt (% )6881 HK Cgs-H 11.02 2,404 50.0 10.26837 HK Haitong Securi-H 22.25 4,285 60.9 9.66030 HK Citic Securiti-H 31.75 4,827 49.0 9.13898 HK Zhuzhou Csr-H 33.35 2,355 8.9 6.71186 HK China Rail Cn-H 9.44 2,529 21.5 6.61099 HK Sinopharm-H 28.05 4,317 20.6 6.51766 HK Csr Corp Ltd-H 7.89 2,060 9.5 6.1728 HK China Telecom-H 4.68 8,379 37.4 6.03323 HK China Natl Bdg-H 7.55 2,805 19.5 5.5941 HK China Mobile 93.85 246,945 220.5 5.4914 HK Anhui Conch-H 27.35 4,586 45.9 5.2371 HK Bj Ent Water 4.69 5,269 8.0 4.9386 HK Sinopec Corp-H 6.5 21,396 109.1 4.8762 HK China Unicom Hon 11.02 34,011 61.6 4.5857 HK Petrochina Co-H 8.52 23,192 113.5 4.5392 HK Beijing Enterpri 59.25 9,818 12.6 4.4

JPHCHBK2 JPHCHSOE

6M 105% call (offer) 5.45% 5.10%

Implied volatility 28.0% 26.0%

6M 105%-120% call spread (offer) 3.45% 3.40%

Savings vs outright call 36.7% 33.3%


44



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 past five years.% Thousand


Figure 98: Rolling backtest of 6M ATM outperformance option on HSCEI vs. HSI over past five years.% Index


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, thegeneral 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.

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HSCEI vs HSI 6M ATM Outperformance

45



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 Correlation


Figure 100: Long quanto vs. short struck call strategy can generate profits when equity-FX correlation breaks down Net Payoff % Option Payoff %




46



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 pricesRe-based Index Level US$/bbl

Source: J.P. Morgan Equity Derivatives Strategy, Bloomberg.*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.

Table 11: Composition of India Low Oil Beneficiaries Basket (JPHINLOI)

Source: J.P. Morgan Equity Derivatives Strategy, Bloomberg. *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 tradesUSD 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 NIFTY 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.



47



Figure 102: Monthly hedging performance via NIFTY futures andput options (based on monthly data from Jan-12 to Nov-14)

Source: J.P. Morgan Equity Derivatives Strategy, Bloomberg. 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.

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

Source: J.P. Morgan Equity Derivatives Strategy, Bloomberg. 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.

48



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 ETFSXEP vs. XLE price performance (rebased 31-Dec-13)


Figure 105:The XLE less SXEP vol spread has picked up again, but is not as wide as in the October correctionXLE less SXEP 6M ATM volatility spread


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


Figure 107: XLE sub-industry breakdown, integrated Oil and Gas makes up only 35% of the index


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Integrated Oil & Gas,

85.2%

Equipment & Services,

7.3%

Drilling, 1.4%

Exploration & Produc,

3.4%

Refining & Marketing,

0.5%

Other, 2.2%

Integrated Oil & Gas,

34.8%

Equipment & Services,

17.8%

Exploration &

Production, 28.6%

Storage & Transport,

7.4%

Refining & Marketing,

7.9%

Drilling, 2.6%

Coal & Consumable Fuels, 0.9%

49



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.

50



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


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


10%

15%

20%

25%

30%

35%

40%

45%

50%

2010 2011 2012 2013 2014

Financials sector ETF 6M ATM implied vol

-6%

-3%

0%

3%

6%

9%

12%

2009 2010 2011 2012 2013 2014

Financials-Materials 6M ATM Spread

1M 3M 12M

ARCC ARES CAPITAL COR Asset Management & Custody Ban Richard Shane Jr OW $15.1 $18.5 7.0% $4,752 $34 -5.5% -6.5% -4.1% 0.89 6.7% 10.4% N/A

BK BANK NY MELLON Asset Management & Custody Ban Vivek Juneja N $39.9 $39.0 7.8% $44,938 $204 0.5% 0.5% 23.8% 1.14 10.7% 1.7% 1.6%

BAC BANK OF AMERICA Diversified Banks Vivek Juneja OW $17.1 $18.0 7.8% $180,147 $1,364 -0.6% 2.3% 13.1% 0.76 2.7% 0.7% 1.8%

COF CAPITAL ONE FINA Consumer Finance Richard Shane Jr OW $80.2 $95.0 7.8% $44,572 $243 -1.7% -0.6% 13.9% 0.94 0.9% 1.5% 1.9%

CME CME GROUP INC Specialized Finance Kenneth B Worthington N $87.1 $84.0 7.8% $29,332 $144 2.3% 10.3% 15.0% 1.34 13.4% 5.1% N/A

CMA COMERICA INC Diversified Banks Steven Alexopoulos OW $44.4 $56.0 7.8% $7,973 $78 -9.1% -13.0% -0.9% 1.01 2.3% 1.8% 3.2%

DFS DISCOVER FINANCI Consumer Finance Richard Shane Jr N $61.8 $65.0 7.8% $28,030 $159 -6.4% -0.6% 19.4% 2.28 4.9% 1.5% 4.6%

LNC LINCOLN NATL CRP Life & Health Insurance Jimmy S Bhullar N $55.0 $62.0 7.8% $14,291 $108 -1.9% 0.6% 10.1% 0.83 6.0% 1.2% 2.9%

LPLA LPL FINANCIAL HO Investment Banking & Brokerage Kenneth B Worthington OW $41.8 $50.0 7.5% $4,130 $39 -2.3% -12.0% -1.5% 3.88 9.3% 2.3% 4.5%

MET METLIFE INC Life & Health Insurance Jimmy S Bhullar OW $52.8 $63.0 7.8% $60,006 $320 -4.2% -4.2% 5.9% 0.83 5.1% 2.5% N/A

RF REGIONS FINANCIA Regional Banks Vivek Juneja N $10.0 $10.0 7.8% $13,779 $166 -1.5% -2.8% 7.0% 0.79 1.9% 1.8% 2.5%

SCHW SCHWAB (CHARLES) Investment Banking & Brokerage Kenneth B Worthington N $28.8 $36.0 7.8% $37,541 $222 -0.1% -2.4% 17.0% 2.97 19.1% 0.8% -0.7%

SIVB SVB FINANCIAL GR Regional Banks Steven Alexopoulos OW $108.5 $140.0 7.8% $5,516 $43 -5.0% -6.3% 8.5% 1.81 3.7% N/A N/A

SPX S&P 500 -1.6% 1.4% 15.1% 2.0% 2.3%

S5FINL S&P 500 FINANCIALS -0.2% 3.6% 16.3% 1.8% 1.6%

1Y Fwd

P/B

1Y Fwd

EPS

Growth

Div

Yield

Buyback

Yield

Price MomentumTicker Name Analyst Rating Wgt (%)Price

Mkt. Cap

($M)

3M

ADV

($M)

Price

TargetIndustry

51



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

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, andover 70% over the last 12 months.

Figure 112: Delta (DAL) 3M ATM implied vol looks relatively cheap vs. history

Source: J.P. Morgan Equity Derivatives Strategy, Bloomberg. Note: AAL data goes back only till 12/09/13

1M 3M 12M

ALASKA AIR GROUP Jamie Baker UW $55.8 $62.0 5.0% $7,402 $84 -0.4% 18.3% 56.0% 11.4 19.8% 0.9% 1.8%

ALLEGIANT TRAVEL N/A NC $135.5 N/A 1.6% $2,369 $21 1.2% 7.8% 29.3% 16.5 38.2% N/A 3.4%

AMERICAN AIRLINE Jamie Baker OW $50.0 $80.5 24.2% $35,842 $742 15.1% 33.1% N/A 6.2 40.9% 0.4% N/A

DELTA AIR LI Jamie Baker OW $47.7 $73.0 27.0% $39,905 $739 9.9% 20.4% 70.4% 10.7 37.9% 0.6% N/A

JETBLUE AIRWAYS Jamie Baker N $14.8 $18.5 2.9% $4,322 $142 18.2% 21.5% 68.9% 12.3 67.5% N/A -0.2%

SOUTHWEST AIR Jamie Baker N $41.4 $52.0 19.0% $28,107 $401 5.3% 22.4% 122.0% 15.3 38.6% 0.5% 1.6%

SPIRIT AIRLINES N/A NC $68.1 N/A 3.3% $4,957 $95 -13.1% -2.9% 57.1% 15.0 41.9% N/A 0.0%

UNITED CONTINENT Jamie Baker OW $64.1 $95.5 16.0% $23,657 $427 17.4% 27.2% 70.4% 8.5 52.2% N/A -0.1%

VIRGIN AMERICA I N/A NC $33.8 N/A 1.0% $1,450 $154 N/A N/A N/A N/A 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%

Price MomentumName Analyst Rating Wgt (%)Price

Mkt. Cap

($M)

3M ADV

($M)

Price

Target

1Y Fwd

P/E

1Y Fwd

EPS

Growth

Div YieldBuyback

Yield

Ticker Airline

Last

Price

Avg daily

notional

traded ($M)

3M ATM

implied vol

3M ATM

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 %


52



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


Figure 114: Energy Beta-adjusted returns and Value seasonality


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

Source: Bloomberg, J.P. Morgan estimates.

60

70

80

90

100

110

200

250

300

350

400

450

500

Dec-13 Feb-14 Apr-14 Jun-14 Aug-14 Oct-14

$/bblcontracts (000s), net non-commercial futures positions

Net long positions

WTI front month price

-1.5%

-1.0%

-0.5%

0.0%

0.5%

1.0%

1.5%

2.0%

Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec

S&P 500 Top Quintile Value S&P 500 Energy

1M 3M 12M

APC ANADARKO PETROLE Oil Comp-Explor&Prodtn Joseph D Allman OW $73.3 $95.0 19.1% $37,143 $459 -18.8% -29.7% -9.0% 23.6 -32.7% 1.3% -0.2%

BWP BOARDWALK PIPELI Pipelines Jeremy Tonet OW $15.8 $24.0 2.0% $3,845 $19 -8.4% -16.6% -34.5% 15.7 6.5% 2.5% N/A

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% 4.2% 25.3 -34.2% 0.6% N/A

DM DOMINION MIDSTRE Pipelines Jeremy Tonet OW $33.0 $43.0 1.1% $2,110 $18 -7.1% N/A N/A 41.0 22.7% N/A N/A

EOG EOG RESOURCES Oil Comp-Explor&Prodtn Joseph D Allman OW $86.4 $109.0 24.3% $47,332 $544 -12.0% -15.6% 11.8% 21.9 -25.8% 0.6% N/A

EQM EQT MIDSTREAM PA Pipelines Jeremy Tonet OW $81.4 $109.0 2.6% $5,040 $26 -10.3% -15.8% 53.7% 19.0 17.9% 2.6% N/A

NBL NOBLE ENERGY INC Oil Comp-Explor&Prodtn Joseph D Allman OW $43.9 $60.0 8.1% $15,871 $137 -19.1% -35.0% -32.7% 19.7 -7.1% 1.5% -0.3%

NS NUSTAR ENERGY LP Pipelines Jeremy Tonet OW $54.5 $74.0 2.2% $4,246 $34 -11.7% -18.6% 16.1% 21.5 19.7% 8.2% N/A

PSX PHILLIPS 66 Oil Comp-Integrated Phil M Gresh OW $65.7 $89.0 18.7% $36,355 $311 -8.6% -19.9% -3.4% 9.3 13.9% 2.8% 5.0%

PXD PIONEER NATURAL Oil Comp-Explor&Prodtn Joseph D Allman OW $131.3 $201.0 10.0% $19,543 $302 -24.0% -35.8% -25.9% 26.3 -4.9% 0.1% N/A

PAGP PLAINS GP HOLD-A Pipelines Jeremy Tonet OW $24.3 $35.0 7.6% $14,708 $45 -14.7% -22.7% 0.2% 39.1 33.3% 2.8% N/A

SPX S&P 500 0.0% 2.4% 16.6% 2.0% 2.3%

S5ENRS S&P 500 Energy -12.7% -18.8% -8.6% 2.9% 2.7%

Buyback

YieldIndustry

Price MomentumMkt. Cap

($M)

3M ADV

($M)

1Y Fwd

P/E

1Y Fwd EPS

Grow thDiv YieldTicker Name Analyst Rating Wgt (%)Price

Price

Target



53



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 non-financials 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 100-110% Skew 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%


Figure 116: The SX7E ATMF volatility term structure is firmly inverted, while Euro STOXX 50 term structure is currently approximately flatATMF implied volatility term structures


We recommend long SX7E Jun-15 150/165 call spreads, financed by selling 125 strike puts for a premium intake of1.9% (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.

16%

20%

24%

28%

32%

Jan-15 Mar-15 May-15 Jul-15 Sep-15 Nov-15

SX7E

Euro STOXX 50

54



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 Ticker 1Y ATM Call*1Y Risk Reversal

(# of ATM calls per ATM put)*Sustainable Shareholder Yield JPAMSYLD 6.75% 1.30Revenue Exposure JPAMDREV 9.35% 1.12Top Picks JPUSTP15 10.10% 1.04Growth Picks JPUSGP15 9.90% 1.02Value Picks JPUSVP15 9.65% 1.05Income Picks JPUSIP15 6.45% 1.31Short Picks JPUSSP15 8.85% 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


55



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 Ticker1Y Total Return

Swap1Y ATM

Call*1Y Risk Reversal

(# of ATM calls per ATM put)*Eurozone Recovery JPDEER15 3M€ + 38bps 7.45% 1.30Commodity Winners JPDECW15 3M€ + 38bps 7.75% 1.10Sustainable Yield Plays JPDEDP15 3M€ + 41bps 6.00% 1.24Buyback Stocks JPDEBB15 3M€ + 49bps 6.00% 1.21Euro Exporters JPDEEX15 3m€ + 38bps 7.15% 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



56



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 NameYTD

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

57



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 re-rating 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 400Index 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

Source: J.P. Morgan. *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>

Source: J.P. Morgan Equity Derivatives Strategy, Bloomberg. * 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>

Source: J.P. Morgan Equity Derivatives Strategy, Bloomberg. * 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.


Price ($mn) ($mn) Wgt (%)

4681 JT Resorttrust Inc 2594 2,318 9.4 7.8

6952 JT Casio Computer 1706 3,966 38.2 6.9

4021 JT Nissan Chem Inds 2126 2,958 14.5 6.7

9303 JT Sumitomo Warehou 642 1,087 2.6 6.2

4401 JT Adeka Corp 1438 1,288 3.0 6.2

4088 JT Air Water Inc 1809 3,107 5.2 6.1

9533 JT Toho Gas Co Ltd 623 2,940 4.8 6.0

3659 JT Nexon Co Ltd 1002 3,721 7.0 6.0

9744 JT Meitec Corp 3315 931 2.9 5.9

8766 JT Tokio Marine Hd 3620 24,075 81.4 5.8

7988 JT Nifco Inc 3490 1,621 5.6 5.7

6457 JT Glory Ltd 3000 1,780 6.2 5.5

5943 JT Noritz Corp 2018 886 2.9 5.4

4061 JT Denki Kagaku 386 1,554 9.5 5.3

7278 JT Exedy Corp 2885 1,212 3.9 5.0

8219 JT Aoyama Trading 2564 1,360 5.8 4.9

5631 JT Japan Steel Work 420 1,348 10.2 4.6


Price ($mn) ($mn) Wgt (%)

005930 KP Samsung Electron 1231000 165,383 296.6 9.4

012330 KP Hyundai Mobis 235000 20,864 50.8 9.4

055550 KP Shinhan Financia 48850 21,128 37.2 9.4

000270 KP Kia Motors Corp 55600 20,557 58.3 9.4

024110 KP Industrial Bank 16350 8,239 20.3 9.4

086280 KP Hyundai Glovis 301000 10,295 22.2 9.4

000810 KP Samsung Fire & M 294000 12,704 26.7 9.3

010130 KP Korea Zinc Co 407000 7,005 15.4 6.0

011210 KP Hyundai Wia Corp 178500 4,189 18.7 6.0

012450 KP Samsung Techwin 35750 1,732 11.5 6.0

001680 KP Daesang Corp 37350 1,172 7.3 3.0

105630 KP Hansae Co Ltd 36500 1,332 6.3 3.0

000100 KP Yuhan Corp 170500 1,734 5.3 3.0

029780 KP Samsung Card Co 48000 5,072 4.8 3.0

005300 KP Lotte Chilsung 1648000 1,860 4.0 1.5

010120 KP Ls Indus Systems 64800 1,773 3.6 1.5

002270 KP Lotte Food Co Lt 643000 803 2.4 1.5










58



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-sharesand 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

Source: J.P. Morgan Equity Derivatives Strategy. 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

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vs SPX

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vs UKX

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vs AS51

Asia vs

DM

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2Y Variance Spread 9.9% 10.5% 10.2% 2.4% 2.9% 2.7% 6.4%

Variance vs Put 7.4% 6.2% 5.4% 6.4% 5.2% 4.4% 5.8%

2Y Realized Volatility Spread 8.3% 8.1% 7.9% 1.1% 1.0% 0.7% 4.5%

3M Realized Volatility Spread 8.2% 7.6% 8.0% -1.3% -1.9% -1.5% 3.2%

Carry (Implied vs 3M Realized) 5.7% 3.4% 3.2% 2.7% 0.4% 0.3% 2.6%

Put Implied Spread %tile vs Implied History 12.4% 20.8% 8.0% 7.0% 12.4% 1.2% 6.1%

Put Implied Spread %tile vs Realized History 0.0% 0.0% 0.0% 0.0% 0.0% 0.0% 0.0%

59



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. SPXVolatility spread


Figure 118: Implied and realized volatility spreads of KOSPI2 vs. SPXVolatility spread


Figure 119: Implied and realized volatility spreads of Asia vs. DM*Volatility spread

Source: J.P. Morgan Equity Derivatives Strategy. * 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.

Figure 120: Implied and realized volatility spreads of HSCEI vs. UKXVolatility spread


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60



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 realizedvolatility 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


Figure 122: S&P 500 index skew has been diverging from skews on its constituents,


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.

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Spread between avg single stock and index 6M ATM implied vol

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61



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 - 125strike 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 levelsDividend vol as % of like maturity equity implied vol


Figure 124: Sector break down of the 2016 IBES bottom up estimates


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


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62



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

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’s14 See Exxon Mobil Corp - Good Defense in a Downside Scenario, and Chevron Corp - Cash Conservation Levers Likely Pulled Soon

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63



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 long-dated delta 1 instruments are currently trading close to its historical highsEuro STOXX 50 5Y and 1Y mid funding spreads (- borrow)


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 TRS mid levels


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 carryled 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.

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64



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.

Figure 129: Nikkei history overlaid with deflation periods (shaded)Nikkei 225 index


Figure 130: SX5E 2Y 80 – 100 skew at record low2Y 80 – 100% skew


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%).

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65



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 theprice, unless the FTSE falls > 20% by Jun-15 expiry in which case it becomes an ATM/90% put spread


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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66



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

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 20081Y 85%-95% downside skew spread


Figure 133: 1Y 85%-95% downside skew spread versus 1Y ATM implied volatility for H-shares1Y 85%-95% downside skew spread


HSCEI HSI NKY KOSPI2 SX5E AS51 UKX SPX

1Y 85%-95% Skew (Current) 0.4% 1.0% 1.2% 1.4% 2.0% 2.7% 3.1% 3.3%

%tile since 2008 (Current) 0.0% 0.0% 10.6% 4.0% 1.1% 55.6% 55.8% 74.7%

High since 2008 3.5% 3.6% 3.9% 3.4% 3.9% 3.3% 3.9% 3.9%

Low since 2008 0.4% 1.0% 0.8% 1.1% 1.9% 2.1% 2.5% 2.2%

Short 1Y 1x2 95%-85% Put Ratio Premium -0.03% -0.80% 0.21% -0.86% -0.04% -0.23% -0.07% 0.34%

0.0%

0.5%

1.0%

1.5%

2.0%

2.5%

3.0%

3.5%

4.0%

Jan-08 Jan-09 Jan-10 Jan-11 Jan-12 Jan-13 Jan-14

HSCEI

NKY

SPX

UKX 0.0%

0.5%

1.0%

1.5%

2.0%

2.5%

3.0%

3.5%

4.0%

0% 10% 20% 30% 40% 50% 60% 70% 80%1Y ATM Implied Volatility

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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 changeProfit and Loss (Index Points)


Figure 135: MTM scenario analysis of short HSCEI 1Y 1x2 95%-85% put versus volatility changeProfit and Loss (Index Points)

Source: J.P. Morgan Equity Derivatives Strategy -1000

0

1000

2000

3000

4000

5000

5,000 6,563 8,125 9,688 11,250 12,813 14,375

P&

L (In

dex

Poi

nts)

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Current

After 6M

After 1Y

Current Spot

-300

-200

-100

0

100

200

300

400

-10 -8 -5 -3 0 3 5 8 10

Volatility Shift (Volatility Points)

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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 structuresImplied volatility


Figure 137: Nikkei 225 forward volatility and term structureImplied volatility Term structure spread


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 exposureis 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

5%

10%

15%

20%

25%

1M 2M 3M 6M 9M 1Y 2Y 3Y 4Y 5Y

Nikkei 225

S&P 500-2%

-1%

0%

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2%

3%

15%

20%

25%

30%

35%


Nikkei 225 1Y Forward 2Y ATM Implied Volatility (LHS)

Nikkei 225 1Y-3Y ATM Term Structure Spread (RHS)

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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 haveno 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 beseen 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 skew90—110% skew


Figure 139: Nikkei 225 price and volatility versus the corridor levelsIndex level Volatility

Source: J.P. Morgan Equity Derivatives Strategy -1%

0%

1%

2%

3%

4%

5%


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

15%

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30%

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Nikkei 225 (LHS)50% Corridor (LHS)110% Corridor (LHS)3Y Realized Volatility (RHS)

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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 lowercost/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

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.

Tenor

Strategy

Cost or

Strike 2Y %ile

Cost or

Strike 2Y %ile

Cost or

Strike 2Y %ile

Puts

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%

Put Spreads

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%

Collars/Put Spread Collars

90% Put/Cashless Collar

Strike*104.0% 85% 104.2% 81% 104.0% 61%

95-85-105% Put Spread

Collar (90-80-110% for 1Y)0.5% 32% 0.3% 37% 0.2% 46%

95-85% Put Spread/

Cashless Collar Strike*103.1% 46% 104.3% 37% 107.0% 40%

Put Ladders/Ratios

ATM-95-90% Put Ladder

(ATM-90-80% for 1Y)0.8% 18% 0.0% 28% 1.5% 17%

Costless 1 ATM x2 OTM Put

Ratio Strike95.4% 37% 92.9% 28% 89.5% 27%

3M 6M 1Y

https://jpmm.com/#research.strategy.equity_derivatives

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Additional Basket MethodologyIn 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.

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Possible Risks of Investing in ETFsThe 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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Risks of Common Option StrategiesRisks 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.

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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 forsophisticated 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.

Analyst Certification: The research analyst(s) denoted by an “AC” on the cover of this report certifies (or, where multiple research analysts are primarily responsible for this report, the research analyst denoted by an “AC” on the cover or within the document individually certifies, with respect to each security or issuer that the research analyst covers in this research) that: (1) all of the views 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 any of the research analyst's compensation was, is, or will be directly or indirectly related to the specific recommendations or views expressed by the research analyst(s) in this report. For all Korea-based research analysts listed on the front cover, they also certify, as per KOFIA requirements, that their analysis was made in good faith and that the views reflect their own opinion, without undue influence or intervention.

Important Disclosures

MSCI: The MSCI sourced information is the exclusive property of MSCI. Without prior written permission of MSCI, this information and any other MSCI intellectual property may not be reproduced, redisseminated or used to create any financial products, including any indices. This information is provided on an 'as is' basis. The user assumes the entire risk of any use made of this information. MSCI, its affiliates and any third party involved in, or related to, computing or compiling the information hereby expressly disclaim all warranties of originality, accuracy, completeness, merchantability or fitness for a particular purpose with respect to any of this information. Without limiting any of the foregoing, in no event shall MSCI, any of its affiliates or any third party involved in, or related to, computing or compiling the information have any liability for any damages of any kind. MSCI and the MSCI indexes are services marks of MSCI and its affiliates.

Company-Specific Disclosures: Important disclosures, including price charts, are available for compendium reports and all J.P. Morgan–covered companies by visiting https://jpmm.com/research/disclosures, calling 1-800-477-0406, or e-mailing [email protected] with your request. J.P. Morgan’s Strategy, Technical, and Quantitative Research teams may screen companies not covered by J.P. Morgan. For important disclosures for these companies, please call 1-800-477-0406 or e-mail [email protected].

Explanation of Equity Research Ratings, Designations and Analyst(s) Coverage Universe: J.P. Morgan uses the following rating system: Overweight [Over the next six to twelve months, we expect this stock will outperform the average total return of the stocks in the analyst’s (or the analyst’s team’s) coverage universe.] Neutral [Over the next six to twelve months, we expect this stock will perform in line with the average total return of the stocks in the analyst’s (or the analyst’s team’s) coverage universe.] Underweight [Over the next six to twelve months, we expect this stock will underperform the average total return of the stocks in the analyst’s (or the analyst’s team’s) coverage universe.] Not Rated (NR): J.P. Morgan has removed the rating and, if applicable, the price target, for this stock because of either a lack of a sufficient fundamental basis or for legal, regulatory or policy reasons. The previous rating and, if applicable, the price target, no longer should be relied upon. An NR designation is not a recommendation or a rating. In our Asia (ex-Australia) and U.K. small- and mid-cap equity research, each stock’s expected total return is compared to the expected total return of a benchmark country market index, not to those analysts’ coverage universe. If it does not appear in the Important Disclosures section of this report, the certifying analyst’s coverage universe can be found on J.P. Morgan’s research website, www.jpmorganmarkets.com.

J.P. Morgan Equity Research Ratings Distribution, as of September 30, 2014

Overweight(buy)

Neutral(hold)

Underweight(sell)

J.P. Morgan Global Equity Research Coverage 46% 42% 12%IB clients* 57% 49% 34%

JPMS Equity Research Coverage 46% 48% 7%IB clients* 76% 67% 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.

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"Other Disclosures" last revised November 29, 2014.

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