JPM_Global_Derivatives_T_2012-12-10_1007652

www.jpmorganmarkets.com

Global Equity Derivatives & Delta One Strategy10 December 2012

Global Derivatives Themes2013 Outlook for Equity Derivatives

Global Head of Derivative & Quantitative Strategies

Marko Kolanovic AC

See page 38 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. In the United States, this information is available only to persons who have received the proper option risk disclosure documents. Please contact your J.P. Morgan representative or visit http://www.optionsclearing.com/publications/risks/riskstoc.pdf.

For the first time in seven years there were no large spikes in the VIX as low volatility in 2012 surprised investors. The key drivers of volatility were the European debt crisis in H1, central banks’ actions in late summer, and concerns about the US fiscal cliff in the fall. Scratching below the surface of the low S&P 500 volatility, one discovers a troubling picture of record-low stock volatility and high correlations—both are potentially damaging to fundamental stock investors. This environment was a result of a downward spiral of low volumes, macro uncertainty, declining participation of fundamental investors, and fund outflows.

In 2013 the prevailing macro uncertainty should provide a floor to volatility. Our quantitative analysis shows that the current low VIX level is in stark contrast to virtually every macroeconomic indicator across the globe. We believe that structural drivers will keep the average level of stock correlation high. Given the already record-low levels of stock volatility, S&P 500 volatility is likely to increase from current levels near term.

Buoyed by central bank actions and macro uncertainty, assets traditionally perceived as safe reached record levels. Not only have equities underperformed, but stocks had lower volatility than gold or long-term bonds. Medium term, flow of assets into equities should cause outperformance and mitigate downside risk. Similarly, implied volatility premium may come under pressure from the continued search for yield.Investors currently overweight traditional safety assets can likely lower risk and increase yield by allocation to high-quality, dividend yielding, inflation-resistant stocks and overwriting strategies.

In the second part of this report, we recommend a number of trade ideas that incorporate our market and volatility views. In particular, we suggest the following Volatility Relative Value Trades: Asia versus DM volatility spreads, long 2014 Euro STOXX 50 dividend volatility, improved volatility carry strategies, taking advantage of flat skews, dispersion; Macro/Directional Trades: Euro STOXX 50 vs. S&P 500 call spreads, EM Asia vs. US outperformance, S&P 500 ratio risk reversals, buy calls on MSCI Mexico, Turkey vs. S. Africa call switch, Nikkei dividend steepeners; Downside Protection Trades: cheapest index put hedges, Jan VIX calls spread funded by selling puts, Japan equity put contingent on rates, FTSE/GBP dual-digital.

Global Equity Derivatives & Quantitative Strategy

Marko KolanovicAC (Global)

(1-212) 272-1438

[email protected]

J.P.Morgan Securities LLC

Davide Silvestrini (EMEA)

(44-20) 7134-4082

[email protected]

J.P.Morgan Securities plc

Tony Lee (Asia Pacific)

(852) 2800-8857

[email protected]

J.P.Morgan Securities (Asia Pacific) Limited

Ruy Ribeiro (Rule-based)

(44-20) 7134-0626

[email protected]

J.P.Morgan Securities plc

Equity Derivatives Strategy Team

US

Marko Kolanovic [email protected]

Bram Kaplan [email protected]

Amyn Bharwani [email protected]

EMEA

Davide Silvestrini [email protected]

Ruy Ribeiro [email protected]

Peng Cheng [email protected]

Carmen Firescu [email protected]

Sahil Manocha [email protected]

Asia Pacific

Tony Lee [email protected]

Sue Lee [email protected]

Hayato Ono [email protected]

Japan

Michiro Naito [email protected]

2


Marko Kolanovic(1-212) [email protected]

Table of ContentsOutlook for Macro Volatility and Correlations .......................3

Outlook for Equity Risk ..........................................................................................3

Cross-Asset Portfolios .............................................................................................7

Implied Correlation .................................................................................................9

Skew and Convexity..............................................................................................12

Term Structure ......................................................................................................16

Dividends..............................................................................................................19

Derivatives Ideas for 2013 .....................................................23

Macro/Directional Trades......................................................................................29

Downside Protection Trades..................................................................................34

Risks of Common Option Strategies ......................................................................37

3



Outlook for Macro Volatility and Correlations

Outlook for Equity Risk

Low levels of volatility in 2012 came as a surprise to investors used to years of market turmoil. At the time of writing our 2012 Outlook, S&P 500 volatility was 31% and we predicted it to decline to a 15-20% range.1 Volatility in 2012 declined below our target and currently stands at 14%, in line with the median level over the last 100 years. For the first time in seven years, there were no large spikes in the VIX (as measured by the ratio of Maximal and Average level) and the VIX itself was range-bound, with the lowest dispersion of levels since 2006 (Figure 1). The key drivers of the market volatility were a deterioration of the European sovereign debt crisis in H1 (Spanish sovereign spreads, Greek elections), followed by accommodative actions of central banks (Draghi’s speech at the end of July, ECB’s OMT and Fed’s QE3 in September). In the last quarter of 2012, market focus started shifting from Europe to the US, where potentially large fiscal adjustments known as the ‘fiscal cliff’ are risking a decline in the stock market or even another US recession(see Impact of Tax Rates on Stock Market Returns).2 In 2012, the premium of the VIX over short-term realized volatility was above its long-term average (2012 average of 5.1 points vs. 20-year average of 4.4), but collapsed post US elections and is now close to zero (Figure 2). The low levels of realized volatility and premium are counterintuitive, given the US fiscal uncertainly and negative growth in Europe. As we will argue below, they are a result of the unique macro environment and significant changes in market microstructure.

Scratching below the surface of the low headline level of the VIX and S&P 500 realized volatility, one discovers a troubling picture of record low volatility of individual stocks and very high levels of correlation between them. In fact, the average volatility of individual S&P 500 stocks is at 30-year lows.3 What appears to be a benign environment with moderate levels of the VIX is a result of an extreme regime of low stock volatility and high market correlations, both of which could prove very damaging for fundamental stock investors4 (Figure 3). This unique microstructure is a result of adownward spiral of low equity volumes, macro uncertainty, declining participation of fundamental stock investors,and fund outflows.

1 6M realized volatility of S&P 500 daily returns.2

The full fiscal cliff amounts to $700bn in 2013, or ~4.5% of GDP. The risks of a larger adjustment and adverse market reaction are substantial.3 On November 1, average 3M volatility of stocks in the S&P 500 reached 18%, the lowest level in over 30 years.4 See Why We Have a Correlation Bubble.

Figure 1: In 2012, the highest level of the VIX was 1.5 times itsaverage, and standard deviation was 2.7 points (inset table). This was the most benign volatility environment since 2006

Source: J.P. Morgan Equity Derivatives Strategy.

Figure 2: VIX and 1M S&P 500 realized volatility. The key drivers of volatility were the European crisis, and actions of central banks. The premium of VIX over realized volatility recently dropped to zero


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Equity share volumes are currently near record lows. Historically, low equity volumes cause low equity volatility (and vice versa), which can help explain the decline in stock volatility (Figure 4). On the other hand, macro uncertainty and macro trading based on central bank policy typically drive Index and Index derivatives volumes higher (Futures, ETFs, Index options) and hence increase stock correlations (see Why We Have a Correlation Bubble, Rise of Cross-Asset Correlations).

The record low equity volumes in 2012 reflect even lower participation of active fundamental investors as ~55% of volume is executed by High Frequency Trading programs (HFT) and ~30% is traded in Exchange Traded Funds (ETFs). While there is a significant overlap between ETF and HFT participation, it is clear that a very small fraction of already low equity volumes are due to fundamental stock investors. HFT trading typically employs index arbitrage, statistical arbitrage, and automated market making, and these strategies further increase correlation and sap stock volatility.

As the spiral of high correlation and low stock volatility makes fundamental investing difficult, long/short stock investors walk away from the market, and equity investments flow into passive (indexation) strategies. In addition to the shift from active to passive or algorithmic strategies, funds further flow out of equities and into the fixed income space, buoyed by their perceived safety and central bank interventions. For instance, Investment Company Institute (ICI) data show that over the past four years, US equity funds recorded $400bn of outflows, while fixed income funds recorded $1,000bn of inflows.

While political risk was the key driver of market performance and volatility, derivatives positioning often had a notable impact on intraday price action and volatility. On September 6 and 13, ECB and Fed announcements caused the market to gap up and a sharp drop in volatility. For several weeks before and after these announcements, the S&P 500 was range-bound around the 1400-1450 levels (Figure 5). Earlier in the year, when the market was ~1300, many investors sold call options at these levels as a part of overwriting or collaring strategies. This caused dealers to be long options (long gamma), and their hedging activity suppressed market realized volatility in August and September, around the 1400 and 1500 levels, in effect similar to a pinning (for details on the mechanics of option hedging impact see Market Impact of Derivatives Hedging).

In November, market performance and volatility were dominated by the US election and concerns around the fiscal cliff. On November 7 the market dropped by 33 points after President Obama was re-elected (note that the size of the election move was almost exactly predicted by the S&P 500 term structure as we noted in Election Day Expected Move). During September and October, investors accumulated long put option positions below 1400, which made dealers short options (gamma) below 1400. As the market dropped below 1400, hedging of short option positions created a predictable “end of the day momentum” effect and subsequent reversal on November 7, 8, 9, and 13, increasing the daily market volatility (Figure 6). Short positioning in S&P 500 options and VIX products did not cause a large increase in market volatility in November. However, we believe there is still a significant overhang of short positions on S&P 500 options and VIX products that could increase volatility if the market drops and the VIX term structure inverts.

Figure 3: What appears to be a benign environment of moderate levels of the VIX is a result of record low stock volatility and high correlations, both of which could prove damaging for fundamental stock investors.


Figure 4: Equity share volumes are currently near record lows. Historically, low equity volumes cause low equity volatility (and vice versa).


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The cost of owning option- and VIX-based hedges has been declining throughout the year.5 The decline in the cost of derivative protection is a result of investors scaling down hedges due to their poor performance, selling of premium to generate yield, overall low levels of equity exposure, and a larger risk complacency post ECB and Fed actions.Holding equity protection in 2012 was very expensive. This can be illustrated by a 70% annualized drop in the VXX just on account of term structure rolldown, and an average 30% loss on long option positions on account of low realized volatility (e.g., 1Y volatility averaged 20%, and realized was 14%). Given the high cost, demand for hedging waned (especially in the second half of the year). As central banks pushed real rates on bonds into negative territory, many investors started outright selling volatility to generate yield. The perception of lower systemic risk prompted investors to sell the volatility premium (e.g., overwriting, short variance strategies) and volatility term structure (e.g. VIX roll-down strategies).

In order to forecast volatility in 2013, we start by estimating the likely macro environment and stability of high equity correlation. The European sovereign debt crisis, and more generally the debt problems of the developed world,should continue to be the main source of macro risk. Compared to a year ago, debt to GDP ratios for most of the developed world countries have increased. While the budget deficits have modestly declined, they are still significant (Figure 7). The uncertainty related to the debt crisis and low expected GDP growth rate6 should provide a floor to market volatility. At this point in time, it is not clear how the US fiscal cliff will be resolved, but we do know that it can have a significant implication on equity markets and the rating of US sovereign debt (e.g., large changes in capital gain, dividend,and small business tax rates can have a meaningful impact on stock market performance and volatility, see Impact of Tax Rates on Stock Market Returns).

To compare the current VIX levels to macro fundamental risk, we have performed a simple quantitative exercise: we compiled a list of 484 macro indicators published by Bloomberg that have a significant correlation to the VIX index and regressed them against the current reading of the VIX. Results show that the current low VIX level is in stark contrast to virtually every macroeconomic indicator across the globe. These indicators include PMI, GDP, payroll and unemployment, housing, retail sales, consumption, inventory, business and consumer confidence, delinquencies, and other economic activity indicators. The 81 US macro series point to a VIX level on average 7.2 points higher, the 214 European indicators point to a VSTOXX level 9.7 points higher, and the 186 Asia economic indicators point to a VNKY level 8.9 points higher (Figure 8). While these results don’t signal an imminent increase in the VIX, they do point to a large discrepancy between the market volatility and macro fundamentals. As we do not think that the macro environment will drastically change over the next year, we believe risk for market volatility is to the upside.

5 The cost of option hedges is measured by the premium of implied volatility over realized volatility (Figure 2), and the cost of being long the VIX is measured by the steepness of the term structure.6 Expected GDP growth for US: 1.7%, Europe 0.0%, Japan 0.0%, Asia-ex 6.5% (see Global Markets Outlook and Strategy).

Figure 5: ECB and FED announcements were key drivers of market performance and volatility in September. Hedging of long S&P 500 option positions suppressed volatility around 1400 and 1450 levels

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

Figure 6: US Elections were key drivers of market performance and volatility in November. Hedging of short S&P 500 option positions increased volatility below the 1400 level





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Next we focus on market correlations. Over the past 20 years, correlation between stocks showed not only a strong cyclical behavior but also a secular increase from levels of ~20% to the current average level of ~40% (see Why We Have a Correlation Bubble). In addition, the volatility of correlations has increased substantially (Figure 9). We believe that the prevailing macro uncertainty and structural drivers described earlier in this section will keep the average level of stock correlation high. Given the already record low levels of stock volatility, we believe S&P 500 volatility is likely to increase from current levels. Our 2013 forecast for average realized volatility is 16% (up from the current 14%) with a most likely range of 14-19%. We believe the VIX will trade at an average premium of 4 points over realized volatility, which is lower than 2012 average premium of 5 points.

Figure 10 shows S&P 500 realized volatility (vertical axis) against average stock volatility (horizontal axis) over the past 20 years. The current level of stock and S&P 500 volatility is illustrated by a red dot. As stock volatility increases, S&P 500 volatility typically increases as well, and the rate of increase is determined by the level of correlation. During periods of low correlations, such as during the Tech Bubble in 2000, substantial increases in stock volatility led only to modest increases inS&P 500 volatility. However, in 2008 and especially 2011, the high level of correlation translated even small increases of stock volatility into significant increases of S&P 500 volatility. The still-high correlation environment leads to higher risk of a volatility spike going forward, in our view.

The risk to our view is that volatility stays at current low levels or decreases further. For volatility to decrease, we would need to see a meaningful decrease in stock correlations, which we think is unlikely. Even if HFT activity declines (as expected by Tabb group), and index volumes decline, stock correlations would likely stay elevated. The reason for this is

Figure 7: Debt and Deficit (as % of GDP) for 10 developed world countries with largest amount of debt outstanding


Figure 8: Based on the past 10 years of historical data, macroeconomic indicators across the globe unambiguously point to a higher level of the VIX


Figure 9: Over the past 20 years, correlation between stocks experienced a secular increase from ~20% to the current average level of ~40%


Figure 10: S&P 500 realized volatility (vertical axis) vs. average stock volatility (horizontal axis). Current level is illustrated by a red dot. There are many different ways for volatility to increase


Country Latest Year ago Change 2012 2011 % Chg.

Japan 214% 207% 7.5% -9.9% -9.5% 4%

USA 103% 99% 4.1% -8.3% -9.7% -15%

Italy 126% 122% 4.4% -1.7% -3.8% -55%

UK 86% 83% 3.2% -7.7% -8.4% -8%

France 91% 86% 5.0% -4.5% -5.2% -14%

Germany 83% 81% 1.7% -0.9% -1.0% -11%

Spain 76% 67% 9.3% -5.4% -8.5% -37%

Canada 86% 84% 1.8% -3.5% -4.5% -24%

Belgium 103% 98% 4.9% -2.8% -3.9% -28%

Netherlands 68% 64% 4.0% -4.3% -4.6% -7%

Debt (% of GDP) Deficit (% of GDP)

10Y Regression of VIX USA Europe Asia

Against Macro Data VIX V2X VNKY

# of Macro Indicators 81 215 188

# point Volatil ity Cheap 81 214 186

# point Volatil ity Rich 0 1 2

Average Points Cheap -7.2 -9.7 -8.9

Standard deviation 2.5 3.3 3.5

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because HFT and index trading are essentially only a transmission mechanism and not the principal source of high correlation. The main source of high correlations is macro uncertainty and political risk that is driving the prices of all risky assets. This becomes obvious if one looks at the evolution of correlation of Equities to Interest Rates, Commodities, and Currencies (Figure 11).7 The correlation of equities to other asset classes has increased dramatically since 2008 as the price of risky assets became largely dependent on the resolution of sovereign debt problems, growth expectations, and monetary policy.

Cross-Asset Portfolios

Equity volatility and correlations are important inputs for the asset allocation process. The described macro and political risks are not only driving cross-asset correlations but also the relative performance of risky assets. Treasury bonds and gold reached record levels, as these assets were directly impacted by central bank actions (outright purchases, inflation hedges). For instance, Treasuries have added almost 10% of pure alpha annually since QE2 (Figure 12). As this outperformance is not based on economic fundamentals, medium term, it is expected to reverse and cause outperformance of equities relative to Treasuries and gold. Not only have equities underperformed these assets, but over the past year, equities have been less risky: volatility of the S&P 500 was 14%, 20Y Bond volatility was 15%, and volatility of gold was 17%. In addition, in the scenario of increased inflation expectations, equities are expected to outperform bonds. We believe that beyond the potential near-term equity weakness and increased volatility, medium term, inflows into equities should cause outperformance over bonds and gold and hence put a ceiling on equity volatility. Similarly, the implied volatility premium may come under pressure from fixed income investors searching for yield. Given the prospect of negative real yields, they may engage in selling equity options and volatility, buying dividends, and other short equity risk premium trades.

Investors that are currently overweight bonds and gold can likely lower their risk by increasing allocation to stocks. Stocks should be chosen from the high-quality and low-volatility universe, and sectors resistant to inflation (Figure 13). To generate yield, investors can increase allocation to high dividend yielding stocks and overwrite positions by selling call options. Overwriting would not just increase yield but would also significantly cut the risk (e.g., selling at-the-money call option would reduce equity risk by ~50%). Given the medium-term risk of inflation, and what appears to be inflated prices of traditional relatively safe assets, we believe that these equity strategies may provide a more robust relative“safe haven” than investing in government bonds or gold.

7 For a detailed review of cross-asset correlations see our report Rise of Cross-Asset Correlations.

Figure 11: Similar to correlation between stocks, correlation of stocks to other asset classes increased as a result of macro uncertainty and monetary policy responses.


Figure 12: Treasury bonds and gold reached record levels as these assets are supported by central bank actions and investors’ fear of inflation. For instance, Treasuries have added almost 10% of pure alpha annually since QE2.


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Despite modest levels of market volatility, we believe there is still a meaningful risk of a tail event in 2013. On the downside, triggers could be the failure to resolve the US fiscal cliff, leading to a debt downgrade and recession, rapid deterioration of the crisis in the Eurozone, or geopolitical escalation in the Middle East. On the upside, a tail event could result from a quick resolution of the US fiscal cliff, upside surprise in global growth, and start of bonds to stocks rotation.

Given the high levels of correlation, cross-asset investors looking to hedge tail risk should compare the pricing of tail hedges in different asset classes. To assess the relative cost of tail risk hedges, we compared long-term historical probabilities (over ~100 years) of realized tail events vs. current option implied probabilities. In particular, Figure 14 shows the ratio of implied to realized tail event probabilities for the S&P 500, Gold, Japanese Yen and 10Y Treasury (for 1M, 3M, 6M, and 1Y time horizons and returns in a -40% to 40% range). Comparing the ratios of implied to realized tail event probabilities across asset classes, we note that in equities, upside tail protection looks cheap and downside tail protection looks the most expensive, compared to other asset classes. This is a result of the supply/demand imbalance for equity index options in which investors are typically buying put options to hedge and selling call options to generate yield or collar positions. Buying far out of the money S&P 500 calls or risk reversals (selling out of the money puts and buying calls) appear to be the cheapest upside tail hedges across-asset classes.

Figure 13: Exposure of sectors to increases in Inflation (CPI). Table shows Z-scores of the response to inflation (from 5 months before to 5 months after an increase in CPI). Positive values indicate sectors that may do well, and negative values indicate sectors that may do poorly in a high inflation environment


Figure 14: Ratio of options implied to historical realized tail event probability in the S&P 500, Gold, JPY, and 10Y Treasury. Equity upside tail protection looks cheap and downside tail protection looks expensive


Sector -5 -4 -3 -2 -1 0 +1 +2 +3 +4 +5

Food Beverage & Tobacco 0.0 0.3 0.9 1.5 1.9 2.4 2.7 2.7 2.8 2.9 2.4

Pharma Biotech & Life Sci. 0.1 0.2 0.7 1.4 1.6 1.9 2.2 2.4 2.5 2.5 2.1

Food & Staples Retailing 0.1 0.8 1.5 1.5 1.1 1.7 2.3 2.5 2.0 2.1 1.8

Utilities 1.0 1.1 1.5 2.0 1.9 1.7 1.7 1.5 1.6 1.6 1.1

Health C. Equipment & Serv. 0.4 0.6 1.2 1.6 1.5 1.5 1.2 0.9 0.8 1.2 1.2

Transportation 0.5 0.3 0.7 1.3 0.9 1.6 1.9 1.6 1.1 0.8 0.4

Energy 2.2 2.1 2.0 2.3 1.8 0.3 -0.1 0.0 0.4 0.1 -0.2

Household & Pers. Prod. -0.1 0.1 0.6 1.0 1.0 1.4 1.9 1.5 1.3 1.2 0.8

Commercial & Prof. Serv. -0.2 0.2 0.4 0.3 -0.1 0.3 1.1 1.8 1.7 1.7 1.6

Telecomms -0.7 -0.3 -0.5 -0.7 -0.8 -0.1 0.4 0.3 0.5 0.6 0.4

Consumer Services -2.7 -2.1 -1.7 -1.6 -1.9 -0.9 0.1 0.6 0.9 1.1 0.9

Retailing -2.0 -1.8 -1.6 -1.2 -1.2 -0.7 -0.1 0.3 0.1 0.6 1.0

Consumer Durable & App. -1.5 -1.6 -1.4 -1.1 -1.2 -0.6 0.3 0.7 -0.2 -0.1 0.1

Capital Goods 1.3 0.9 0.7 0.4 -0.1 -0.2 -0.3 -0.5 -1.0 -1.7 -1.8

Real Estate 0.6 0.3 0.2 0.5 0.1 -0.3 -0.6 -0.5 -1.0 -1.2 -1.1

Semi & Semi Eqipment 0.1 0.0 -0.5 -0.6 -0.2 -0.5 -0.5 -0.3 -0.3 -0.2 -0.2

Materials 0.2 0.1 0.2 0.3 -0.4 -0.9 -1.3 -1.1 -0.7 -0.7 0.0

Insurance 0.3 0.1 0.0 -0.4 -1.4 -1.3 -0.7 -0.4 -0.8 -1.2 -0.9

Banks -1.1 -1.3 -1.5 -1.4 -1.1 -0.1 0.7 0.9 -0.3 -1.0 -0.8

Div Financial -0.4 -1.1 -1.4 -1.6 -1.4 -0.7 -0.5 -0.4 -0.8 -0.9 -0.2

Software & Services -1.0 -1.0 -1.1 -1.4 -0.9 -0.9 -1.3 -1.2 -0.9 -0.6 -0.4

Tech Hardware & Eqipment -0.6 -0.5 -1.1 -1.6 -1.2 -1.3 -1.6 -1.5 -1.3 -1.1 -1.2

Media -1.2 -1.4 -1.6 -1.4 -1.4 -1.6 -1.7 -1.5 -1.5 -1.6 -1.5

Auto & Components -2.0 -1.8 -1.7 -1.9 -1.9 -2.0 -1.8 -1.8 -2.4 -3.0 -2.8

Ratio of Implied to Realized Tail Probability

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S&P 500

1M 4.1 2.8 1.9 0.6 0.2

3M 4.6 3.0 2.4 1.9 0.6 0.4 0.1

6M 7.2 4.3 3.2 2.2 1.8 0.6 0.5 0.2 0.1

1Y 6.4 4.1 3.3 2.1 1.9 0.6 0.5 0.3 0.2 0.2

Average 6.8 4.3 3.4 2.3 1.8 0.5 0.4 0.2 0.2 0.2

GOLD

1M 4.8 1.4 1.2 0.8 0.4 0.2

3M 4.8 1.8 1.4 0.9 0.7 0.6 0.5 0.2

6M 3.5 1.8 1.4 0.8 0.7 0.8 0.8 0.6

1Y 4.1 2.7 1.7 1.5 0.8 0.7 0.7 0.8 0.9

Average 4.1 3.9 1.7 1.1 0.7 0.7 0.6 0.7 0.6

JPY

1M 1.9 0.5 1.1

3M 0.6 0.5 0.9 1.7

6M 0.7 0.5 0.7 1.0 1.2 4.2

1Y 0.8 1.1 0.6 0.7 1.2 1.1 2.4

Average 0.8 0.9 0.9 1.0 1.9 1.3 3.3

10Y Bond

1M 0.4 0.4

3M 0.8 0.5 0.4

6M 0.4 1.0 0.6 0.5 0.6

1Y 0.7 1.0 0.7 0.6 0.4 0.4

Average 0.5 0.8 0.6 0.5 0.5 0.4

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Implied Correlation

In the previous section we discussed our view that stock correlations will stay elevated on account of macro uncertainty and the structural impact of HFT and elevated index trading activity. Despite high levels of realized correlation, implied correlation in 2012 has been trading at a significant premium relative to realized correlation for the S&P 500 (Figure 15). This was also the case for most global indices (Figure 16). During the bull market of 2003 to 2007, correlation was one of the more popular volatility arbitrage trades. By selling correlation, hedge funds provided liquidity needed to meet demand for index protection and at the same time absorbed excessive supply of single-stock volatility coming from overwriting programs and structured product issuance. While selling correlation is an arbitrage trade that in principle can be made market and volatility neutral, the trade has higher order volatility exposures that usually make it short volatility (e.g., see Dispersion Trading and Volatility Gamma Risk). Moreover, during volatility spikes, index volatility tends to react faster than stock volatility, and this can lead to additional short volatility exposure. For these reasons, correlation trades, like other volatility carry trades, worked extremely well during the low volatility period of 2003-2007.

Figure 15 : Despite high levels of realized correlation, implied correlation in 2012 has been trading at a significant premium relative to realized correlation for the S&P 500


Figure 16: Implied and realized correlations across global indices declined throughout the year from the elevated 2H11 levelsAvg implied and realized correlation for 8 major global indices*


* S&P 500, Euro STOXX 50, FTSE, DAX, SMI, TOPIX Core 30, ASX 200, Hang Seng.

Since 2009, the correlation premium has stayed high, but volatility of correlation has increased substantially, increasing the risk for short correlation positions (see Expecting a Near-Term Decline in Stock Correlations). In particular, volatility of realized correlation post 2008 almost doubled to an average volatility of 14 correlation points (Figure 17).

In addition to higher risk for correlation trades, the potential return has diminished, despite the high implied-realized correlation spread. To understand these dynamics, one needs to look at the mechanics of correlation trades. Correlation trades are nowadays implemented by trading variance or volatility swaps (rather than correlation swaps). At high levels of correlation and low levels of stock volatility, capturing the same spread of implied to realized correlation translates into less actual PnL as expressed in point gains on volatility or variance swaps. For instance, Figure 18 shows that to capture 1 vega profit on the stock volatility leg, the implied-realized correlation spread that needs to be captured is twice as high now compared to the period prior to the 2008 crisis. Similar is true for capturing profit on the index volatility leg. The same analysis applies to the bid-offer spread investors need to pay on a correlation trade. For instance, paying a 2 vega bid-offer spread on single stock variance pre-crisis would translate into 4 correlation points, while now it takes away 8 correlation points from the trade.

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Figure 17: Dispersion of realized correlation levels doubled post 2008 crisis, increasing the risk for short correlation trades


Figure 18: High levels of correlation and low levels of stock volatility reduce the profitability of correlation trades as the same implied-realized correlation spreads translate into lower profits on the trade


Given the high levels of correlation and low level of volatility, the potential for profit in correlation trades decreased post-2008 relative to the 2003-2007 time period (or alternatively to keep the same profitability, investors needed to significantly increase the risk). At the same time, volatility of correlation increased, further reducing the risk-reward attractiveness of short correlation trades. The attractiveness of correlation trades also decreased relative to other carry trades. For instance,during 2012, capturing 1Y correlation premium would have resulted in approximately 3 index point Vega, while sellingVIX 4M-7M term structure would have resulted in a ~6 Vega annual profit, at a comparable level of market risk and lower liquidity risk.

Looking into 2013, we believe that investors should be more selective with regards to correlation/dispersion trades as opportunities are scarcer. In the sections below we highlight where we think the attractive trades lie:

Europe: For 2013, the multi-year low skew has rendered short correlation trades unattractive at the moment for EuroSTOXX 50 and DAX, in our view. However, we note that the FTSE 100 and SMI remain outliers with a different dynamic.

Although the absolute level of implied correlation is lower now, FTSE still presents a good opportunity, mainly in its skew differential versus its single-stock constituents. Index skew has rebounded recently, while single-stock skew had its biggest drop in two weeks. Therefore, investors can currently buy the volatility spread between the index and single stocks’ 90% strike options at an attractive level of ~4.8%, while it is realizing ~6.5%. This trade idea is detailed further in the Volatility Trades section of the report.

The SMI represented another interesting opportunity for dispersion trades in 2012. Dynamics in this market were mostly driven by the EUR/CHF peg and investor fears that the SNB would be unable to cope with the amount of FX reserves required to maintain its currency peg to the EUR at 1.20. After the ECB’s intervention and EUR/USD rally, these worries abated, and EUR/CHF volatility collapsed (with ATM trading ~1.9% volatility). During the course of the year, SMI volatility showed similar patterns to EUR/CHF volatility; however, SMI volatility lagged the retracement in EUR/CHF volatility. It is exactly this delay that created trade opportunities in SMI dispersion in late August/September as the SMI index volatility and skew appeared rich, while its constituents’ vols were trading considerably cheaper, in line with economic fundamentals and currency risk.

In their 2013 FX Outlook, our FX strategists remain cautious on EUR/CHF. Their view is that even though most FX markets will be range-bound, they expect the EUR/CHF peg to remain under pressure. This will likely provide opportunities in both EUR/CHF and SMI volatility next year as well as SMI dispersion.

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Asia: With the Fed and ECB policy actions keeping volatility in check, implied correlations across Asia have come down significantly, similar to the pattern in other regions. The modest year-to-date return of 9% for the MSCI Asia Pacific benchmark and index EPS downgrades throughout the year hide a large dispersion in country/sector/stocks returns and the importance of relative EPS revisions driving relative returns. The year 2012 provided a good environment for active managers as indicated by the much lower levels of realized correlations, resulting in the wide implied-to-realized spreads versus levels one year ago. ASX 200 stands out in the region, in terms of implied-to-realized spreads as well as the implied correlation percentile relative to its realized correlation history. The structural drivers of volatility continue to have an impact on correlation as investors look for ways to enhance yield through overwriting activities, which provide abundant single-stock volatility supply. Hence, it is our preferred index for dispersion trades going into 2013 for this region. TOPIX Core 30 is another index that ranks highly as a dispersion trade candidate, largely due to its rich implied-to-realized spread. Going into 2013, with financial repression and QE3/infinity forcing investors to consider equities, P/E multiples are likely to rise while relative EPS revisions will continue to drive relative returns. Under this environment, correlations in Asia should remain under pressure while the implied to realized spread should continue to widen, in our view.

Table 1: Realized and implied correlations for the main global indices

1Y ATM implied correlation

5Y percentile6M realised correlation

5Y percentile

Implied %ile of 1Y realised correlation

1Y ATM vol spread avg single stocks vs. index

SPX 61% 55% 45% 29% 100% 5.1%

SX5E 66% 59% 56% 53% 86% 5.9%

DAX 64% 55% 53% 59% 82% 4.8%

UKX 50% 28% 36% 21% 72% 4.8%

SMI 51% 20% 35% 22% 66% 5.2%

HSI Top 15 56% 4% 49% 17% 29% 5.3%

AS51 Top 15 54% 22% 36% 19% 77% 4.4%

TPCX30 (vs. NKY) 56% 60% 35% 4% 61% 5.9%


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Skew and Convexity

In our 2012 Outlook we highlighted how the cost of downside risk protection was sharply re-priced in the aftermath of the 2008 financial crisis and stood near all-time highs. We further noted that this re-pricing was largely driven by technical factors and overestimated the risk of both downside and upside tail events, and thus we recommended selling the rich skew through a number of derivatives structures. In the last six months, global index skews have dropped significantly and for European and Asian underliers are near post-crisis lows. Figure 19 shows the recent history of skew for several indices globally, illustrating the sharp re-pricing of global skews in the last six months. This picture looks similar for both upside (ATM-110%) and downside (90%-ATM) skews as both the put and call wings have flattened. For example, in Figure 20 we can see how the S&P 500 3M fixed strike skew has flattened from mid June, with both the downside skew coming down and upside skew shifting up, even though the spot index is little changed over the period.

Figure 19: 6M 90%-110% skews of major indices have fallen significantly over the last 6 months6M 90%-110% skew


Figure 20: S&P 500 fixed strike skew flattened on both wings over the last 6 months3M Implied Vol

Strike

Source: J.P. Morgan Equity Derivatives Strategy. Based on data over the past 5 years

The recent repricing of skew is in part attributable to decreased demand for hedges this year, for example evidenced by the sharp decline in the S&P 500 put/call open interest ratio since Q1. The put/call ratio typically rises alongside the market as investors increasingly seek to protect their gains, while when the market falls equity exposure is typically cut, reducing the need for hedging. However, during the latest rally since June, it appears investors bought considerably less protection than historically (Figure 21). We attribute this fall in demand for hedges to:

Low realized volatility—S&P 500 realized volatility is just ~13% YTD. This has caused hedges to underperform and sapped investor demand for continuing to buy expensive volatility in hedging structures.

Investor complacency—The perception of tail risks has waned as investors gained comfort from the idea that central bank actions can cure economic woes, leading to lower protection buying. Markets appear to have put confidence in monetary policy actions as risk parameters (e.g., VIX at 16, skew near post-crisis lows) do not reflect the fact that Europe spent 2012 in recession and US growth was consistently downgraded throughout the year.

Investors’ low equity exposure—For example, ICI fund flow data have shown persistent mutual fund outflows from equities since March; US mutual fund beta to equities dropped to its lowest level since 19988; while our Asset Allocation team shows below-average equity exposure in balanced funds most of the time since Q1.9

Central bank support – after central banks committed unlimited support to markets, the perception of tail risks fell, leading investors to require less protection. This further contributed to the divergence seen in Figure 21.

8 See US Equity Strategy FLASH, 29-Nov-2012 9 See Flows & Liquidity, 8-Nov-2012

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In addition to the low demand for hedging, the search for yield led investors to sell downside through risk reversals, reverse convertibles, and outright variance selling, further compressing skew. Another manifestation of the collapse in skew is the low spot sensitivity of implied volatility this year. The average beta of the VIX to the market over the last six months is one-third lower compared to 2H11, leading implied volatility to underperform the moves that were priced into the (record high)skew earlier this year (Figure 22).

Figure 21: S&P 500 put/call ratio reflects decreased protection buying since Q1Index level Put/call open interest ratio


Figure 22: Vol has become less sensitive to spot moves, leading it to underperform what was priced into the record high skew earlier this year


While in late 2011/early 2012 most indices faced near-record high skew levels, most Asian and European index skews are now near their post-crisis lows (Figure 23). At the time of writing, across major global indices, the absolute level of 6M 90%-110% skew is highest on the S&P 500, followed by the FTSE, Nasdaq, and DAX (Figure 23).

Figure 23: Summary of 6M skews across the globe

6M 90-110% Skew

CurrentGlobal Rank

5Y %ile Avg Max Min

SPX 7.2% 1 42% 7.5% 9.5% 5.3%

NDX 6.0% 3 23% 6.7% 8.7% 3.9%

SX5E 4.5% 7 0% 6.9% 10.0% 4.5%

UKX 6.3% 2 10% 7.4% 9.7% 5.7%

DAX 5.5% 4 1% 6.9% 9.6% 5.3%

SMI 4.6% 6 2% 6.2% 7.7% 4.2%

NKY 0.8% 11 1% 5.5% 9.8% 0.1%

HSI 1.7% 9 0% 4.5% 8.1% 1.6%

AS51 4.8% 5 2% 6.1% 8.3% 4.4%

HSCEI 0.9% 10 1% 4.2% 8.1% 0.7%

KOSPI 1.8% 8 1% 4.9% 7.9% 1.8%

Source: J.P. Morgan Equity Derivatives Strategy. As of 5-Dec-12, and based on data over the

past five years.

US: The S&P 500 has the most liquid option market globally, and many non-US investors use S&P 500 puts to protect against a market decline or downside tail event. Additionally, the S&P 500 has one of the lowest volatility levels among global indices, leading the skew to price in a larger boost to volatility to the downside (and hence steeper skew). Further, the low implied volatility level leads to higher skew when measured in non-normalized terms, since the deltas of the 90% and 110% strikes are lower than on higher volatility indices. Together these factors help explain why S&P 500 skew remains significantly steeper than its international counterparts. In addition to demand for short-dated S&P 500 puts, there is

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incremental demand for long-term variance and long-term out-of-the-money puts (~5Y to 10Y) from the insurance industry. Insurance demand for longer dated skew meets short-term hedging demand at the 1-2Y maturity point, providing support for skew across all maturities. However, insurance demand for long-dated variance/puts has weakened in the latter part of this year, also contributing to the decrease in skew (see the Term Structure section).

Europe: Euro STOXX 50 skew is near post-Lehman lows, likely driven by low investor positioning in Europe as the Eurozone debt crisis wears on, reduced perception of tail risk in the region after the ECB finally assumed the role of “buyer of last resort,” and the orderly nature of the year’s main sell-off (the Euro STOXX 50 fell over 20% from March to May, but did so on just 23% annualized volatility). FTSE skew remains elevated relative to other major indices for similar reasons to the S&P 500 (low volatility) and due to its high correlation to the S&P 500. It also reached record skew levels early this year but fell sharply over the summer.

Asia: Driven by the hunger for yield under a prolonged low interest rate environment, domestic retail investors have flockedto structured products for income generation, which offer considerably higher yield than fixed deposits but with a higher possibility of capital being at risk. For Japan and Korea, issuance activities set historical highs this year (see Figure 24 and Figure 25). Recall that the structured products in this region are predominantly volatility-selling in nature, where the couponis funded from the selling of put options that can sometimes have exotic barrier features. The significant growth of this market can lead to an imbalance of volatility supply and demand as the product issuers hedge their long vega exposure, suppressing market volatility and skew (see Figure 19 and Figure 23). Hence it is not surprising to find that skews for Asian markets normalized quickly post the May 2012 correction, particularly in Hang Seng, H-shares, KOSPI 200, and Nikkei 225, where there are active structured product issuance, and are currently among the lowest in the world. Going into 2013, with investors continuing to focus on the search for yield theme, we expect structured product issuance in Asia will remain vibrant, leading to an oversupply of volatility that will continue to suppress the volatility risk premium and skew, while providing interesting opportunities for volatility trading.

Figure 24: Monthly structured product issuance in Korea Monthly issuance (KRW Bn) as of Sep-12 month end KOSPI 200


Figure 25: Annual structured product issuance in JapanAnnual issuance (JPY Bn) as of Sep-12 month end


The price of convexity, as measured by the spread between variance and ATM volatility, has also fallen from record highs across global indices this year but remains considerably more expensive than prior to the 2008 crisis. In light of the drop in skew this year, the fall in convexity is not surprising as skew is a key pricing component of variance swaps. However, as we argued previously, convexity remains elevated due to the reduced capacity of the financial system to store this risk10 and the continued demand for tail risk protection as the 2008 crisis remains vivid in investors’ minds. At the time of writing, across major global indices, the absolute level of 12M convexity is the highest on H-shares followed by KOSPI

10 Regulatory changes in the last couple of years have forced the closure of proprietary trading desks and increased the cost of capital for dealers, reducing the supply of tail risk.

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200 and Nikkei 225. Most major indices’ convexity levels are below their post-Lehman average, with the exception of the ASX 200 (Figure 27).

Figure 26: 12M convexity of major indices12M variance swap strike minus 12M ATM volatility


Figure 27: Summary of 12M convexity across the globe

12M Var-ATM Spread

CurrentGlobal Rank

5Y %ile Avg Max

SPX 4.1% 9 48% 4.0% 7.8%

NDX 4.3% 6 62% 3.8% 8.0%

SX5E 4.1% 7 24% 5.1% 11.1%

UKX 4.5% 5 48% 4.5% 8.1%

DAX 3.7% 10 41% 4.0% 8.2%

SMI 3.4% 11 47% 3.6% 7.1%

NKY 4.7% 3 34% 5.5% 10.9%

HSI 4.5% 4 36% 5.3% 13.1%

AS51 4.1% 8 70% 3.3% 6.4%

HSCEI 5.7% 1 57% 5.9% 12.9%

KOSPI2 4.8% 2 38% 5.1% 11.3%

Source: J.P. Morgan Equity Derivatives Strategy. Based on data over the past 5 years

Although Nikkei volatility and skew are currently depressed to multi-year lows due to the aforementioned structured product-related hedging activities, the price of convexity remains relatively elevated, largely driven by the demand for variance swaps from product issuers to hedge their volga exposure. Similar to index skews, which are often used as a metric of risk premium in the equity derivatives world, convexity reset higher throughout the March 2011 earthquake event and the risk-off period in 3Q11. Unlike skew, convexity remains stubbornly high even after the announcement of QE3, which is effectively perceived as an open-ended put option that has removed tail risks from the market (see Figure 28). In addition to trading at elevated levels, Nikkei convexity shows relative richness when measured against the Derman approximation (seeFigure 29). Given that skew is a major component that affects the pricing of variance swaps (in addition to implied volatility), the current flatness in the Nikkei skew further reinforces the notion that variance convexity is rich, creating opportunities for volatility arbitrageurs.

Figure 28: Nikkei 12M convexity versus 12M 90-110% skewConvexity and skew


Figure 29: 12M variance vs. Derman approx. across major indicesVariance minus Derman approximation


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Term Structure

In 2012, volatility term structures across the globe were upward sloping (normal) for most of the time. Following ECB and Fed easing in September, and the drop in short-term implied volatility, term structure reached record levels of steepness in some major indices such as S&P 500 and ASX 200. Only during the risk-off period following the Greek elections in May did most indices exhibit the inversions in their term structures. However, the inversions were rather modest and quickly normalized, which illustrated perhaps too much risk premium and expectation of volatility being priced in at the time. Although concerns related to the US fiscal cliff led to some flattening, in particular in the short end of the curve, all term structures remain upward sloping. Based on the 12M-3M term structure spread, Nikkei 225 is currently the flattest while ASX 200 is the steepest (see Figure 30). Relative to the history over the past five years, ASX 200 and Swiss Market Index are at the high end of the range with average percentiles of 85% for different parts of the curve while S&P 500 and Nikkei 225 are much flatter with average percentiles of over 60% (see Figure 31).

Despite the ongoing macro uncertainty throughout 2012, equity markets were oscillating with an upward trend amid low realized volatility and low volumes. The environment was very frustrating for option investors as the collapse in risk premium did not improve the carry aspect of long option positions. The very low levels of implied volatility were still relatively rich versus realized volatility, although the calendar was packed with various events that could have become volatility catalysts. Hence, option strategies that can help mitigate the cost of carry or lower the option premium have been very popular. One such strategy is the calendar call spread or put spread, of which our team has been a strong advocate(European Equity Derivatives Weekly Outlook, 12-Jun-12 and Asia Pacific Equity Derivatives Weekly Highlights, 16-Jul-12). The structure consists of buying a shorter dated option and selling a longer dated option, taking advantage of the steep term structure. Depending on the indices, the strikes of the two option legs can also be varied to take advantage of the skew differentials along the term structure. For example, as a protection strategy, investors can consider buying a diagonal put spread, which consists of buying a 3M 95% put while selling a 6M 85% put.

Figure 30: Term structures in 2012 were mostly upward sloping12M-3M Implied Volatility Spread (%)


Figure 31: Term structure spread percentiles over the past 5 yearsTerm structure spread 5Y percentiles (sorted by descending order for 6M-1M)


US: The subdued level of realized volatility in 2012 on the S&P 500 (~13% YTD) has put persistent downward pressure on the short end of the S&P 500 term structure this year. Unlike Asia and Europe, where structured product issuance is the main driver of long-dated volatility, on the S&P 500 long-dated volatility continues to be driven by the demand for long-term variance and long-term out-of-the-money puts (~5-10Y maturity) from the insurance industry to hedge their variable annuity products. 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 2012.

The term structure steepness will be related to realized volatility, and for this reason, the S&P 500 term structure of long-dated variance (i.e., past 1Y) remains steep by historical standards at the time of writing. However, unusually, the fall in implied volatility year-to-date has been close to parallel across the term structure, with long-dated volatilities re-pricing

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materially over the last year (Figure 32). For example, 10-year variance fell from the mid/high 30s late last year to the high 20s at the time of writing, and is close to its post-crisis lows. Typically, longer dated vols move with much lower beta to the shorter end of the curve—over the last five years, the average beta of 10Y to 6M variance was ~30%, while the YTD fall in 10Y variance was ~90% of the move in 6M variance. Long-dated vols have come in strongly over the last few months as demand from traditional insurance buyers waned, and some at times even turned into sellers as some insurers found themselves over-hedged. This has led to a flattening of the long end of the term structure over Q4-12. In our 2012 Outlook, we highlighted the richness of long-dated variance, pointing out that variance strikes beyond two years were higher than was realized at any point since the Great Depression. Now this is only (more narrowly) true beyond five-year maturities.

On the VIX, last year the front end of the term structure was primarily driven by the large investment into directional systematic volatility ETNs like the VXX and TVIX. However, this year, the front-end term structure (2nd-1st month future) diverged from the funds invested in directional strategies (see Figure 33). In our view, this is due to the recent popularity of dynamic VIX strategies that sell the short-dated futures opportunistically to exploit their expensive carry cost and offset part of the systematic flow from the long volatility products.

Figure 32: The SPX variance curve shifted in a near-parallel fashion YTD, resulting in a large beta-adjusted fall in long-term varianceS&P 500 Variance Strike


Figure 33: The VIX front end term structure was less driven by systematic directional strategies like VXX as dynamic strategies gained favorNet vega outstanding for largest VIX ETNs VIX 2nd-1st future spread

(VXX+TVIX+UVXY+VIXY-XIV)


Europe: The Euro STOXX 50 term structure was the flattest/most inverted among major global indices throughout most of 2012 as front-end volatilities priced in continuing near-term risks for the peripheral debt crisis, and due to the index’s relatively high realized volatility. As we predicted in our 2012 Outlook, the bumpy road toward resolution of the Eurozone debt crisis drove Euro STOXX 50 to a much wider than normal realized volatility spread vs. the S&P 500. Year-to-date, the realized volatility spread between the Euro STOXX 50 and S&P 500 was ~8.5% compared to a long-term historical average of ~2.5%.

Meanwhile, longer dated Euro STOXX 50 volatilities are mostly driven by structured product flows. The most popular structures this year were reverse convertibles/autocallables (which sell volatility and skew), followed by capped/uncapped calls (which buy volatility). Reverse convertibles, which sell an OTM (sometimes knock-in) put to fund a coupon, gained in popularity this year as investors desperately searched for yield in a zero rate environment. Despite a significant YoY decline in total European structured product issuance, the popularity of reverse convertible structures likely exerted downward pressure on long-term implied volatilities and helps explain the narrowing term premium (e.g., Euro STOXX 50 3M variance swaps trade at nearly a 5 vega premium to the S&P 500, while 5Y variance strikes only differ by ~1.7 points).

Asia: Overall term structure movements should be directional, in particular in the short end of the curve, as bullish equity markets and low volatility lead to the steepening of the curve (see Figure 34). In the medium to long end of the curve,

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however, term structure should be largely driven by the supply and demand for structured products. With interest rates remaining low for a prolonged period of time, we expect the search for yield theme will continue to be the focus of many investors in 2013. For Japan and Korea, where popular structured products involve the selling of longer dated volatility for yield enhancement, the continued issuance of such products in a low interest rate, low volatility environment would likely depress long-dated volatility further, flattening the term structure at that part of the curve. Hence it is not surprising to see that the 3Y-1Y volatility spreads for KOSPI 200 and Nikkei 225 have been much flatter than that for S&P 500, especially with the issuance of structured products setting record high levels this year (see Skew Section and Figure 35).

Figure 34: Term structure steepens with falling volatilityImplied Volatility Term Structure Volatility Spread (Reverse)


Figure 35: NKY and KOSPI2 3Y-1Y term structures much flatter vs. S&P 5003Y-1Y Implied Volatility Spread


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Dividends

2012 has proven to be a good year for global index dividends as the front-dated expiries generally performed well relative totheir respective equity indices. Looking into 2013, however, we believe there will likely be more divergence in performance between global index dividends as the differentiation in market environments increases. As discussed in detail below, for 2013 we are positive on the FTSE dividends, look for better entry points on the Euro STOXX 50 dividends, remain cautiously optimistic on the Nikkei dividends, and turn neutral on HSCEI and S&P 500 dividends.

Euro STOXX 50 Dividends

Although the Euro STOXX 50 dividend market experienced some major setbacks such as Telefonica’s dividend cut, year to date the 13s and 14s have delivered respectable double-digit returns. This was not the result of a high beta rally since the short-dated futures performed in line with their longer dated peers as well as the Euro STOXX 50 index (Figure 36). On the other hand, dividend returns were dwarfed by the Euro HY bond YTD returns of 26%.

Besides the general compression in risk premium, the driver of the performance across asset classes, in our view, can be largely attributed to investors’ search for yield. Given the low economic growth outlook, the abatement of tail risk in Europe, and suppressed yields on relatively safe assets, credit has become investors’ favored asset class. Within credit, we witnessed the reach for low-quality issues. Looking into next year, investors’ preference is unlikely to change:

European economic growth is expected to slowly pick up by the middle of 2013, but strong growth is unlikely, according to JPM economists. Therefore, growth assets such as equities will likely continue to take a back seat to yielding assets.

On the other hand, we expect yields to remain suppressed due to central bank policies. The Fed’s QE and ECB’s OMT are expected to keep yields low and put a ceiling on volatility.

Under these two opposing forces, we believe dividends will continue to benefit from investors’ hunt for yield in 2013:

Our credit strategists see limited upside in HY credit for 2013 (base case +6% from the current level).

Therefore, we believe the search for yield will lead investors to continue widening their investment universe, i.e.,to peripheral bonds, high dividend stocks, and naturally, dividend futures.

Figure 36: 2012 Year-to-date total returns across asset classes

% YTD return

Source: J.P. Morgan, Bloomberg

Return of dividend futures include 1Y Euribor swap yield

Figure 37: Dividends still trade at an elevated risk premium compared to HY bonds

Credit spread / dividend annualised upside (bps)

Source: J.P. Morgan

To forecast the returns of dividends next year, we decompose the dividend futures prices into two parts and analyze separately: Dividend Futures Price Target = Discount Factor × Bottom-Up Estimates.

42%

30%

21%

15%17% 17% 17%

0%

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20%

30%

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50%

€ CCC € B € BB DEDZ3 DEDZ4 DEDZ8 SX5E TR 0

500

1,000

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Mar 04 Mar 06 Feb 08 Feb 10 Feb 12

2Y Div Futures Upside to IBES

JPM Euro HY spread to worst

20



Discount Factor: As Figure 37 shows, the annualised upside on dividends still trades at elevated levels relative to HY credit spreads, and we expect both to compress next year. In their base case, JPM credit strategists Dulake and team forecast a spread compression of 81 bps for Euro HY bonds from the current level. In Figure 38 we show the historical relationship between the 1Y changes in HY spreads and upside on 1 year dividend futures. Based on this relationship, the change in HY spread should correspond to a compression of 180 bps on the 2014s’ upside, in addition to the pull-to-realized slide of 360 bps, by the end of 2013.

Figure 38: Annual changes in 1 year dividend upside shows strong correlation with changes in HY spreads

Annual changes in 1 year to maturity dividend upside

Annual changes in Euro HY credit spread

Source: J.P. Morgan Equity Derivatives Strategy

Figure 39: Bottom-up estimates have been continually revised down since 2008

IBES bottom up estimates


Bottom-up estimates: As Figure 39 shows, since 2008 analysts have continually overestimated Euro STOXX 50 dividends. We expect this trend to continue for 2014/15 dividends. With the anemic economic growth as previously discussed, JPM equity strategists Matejka and Cau forecast EPS growth of 0% for 2013 and 5% for 2014 in EMU. Therefore, the consensus dividend growth rates of 7% each year still appear high. Using 108.3 as a base case for the 2013s, and applying our equity strategists’ zero EPS growth rate to the dividends, we arrive at a target bottom-up estimate for 2014s of 108.

Combined with the risk premium derived previously, we see a 1Y price target of 105 for the 2014s (6% upside). This compares to the 6% return forecast on Euro HY bonds by our credit strategists and 5% on the MSCI EMU equity index by our equity strategists. Using the same methodology, we see a 1-year price target of 102 (6% upside) for the 2015s.

Downside risks to our base case: Although we believe the dividends will continue to perform well relative to other assets in 2013, we see two main ways a slower than expected economic growth rate in 2013 could impact our base case:

Spanish banks: These are still the biggest risk, in our view. Higher than expected deficits could make the environment more hostile for Santander and BBVA; for example, the Spanish government raising taxes on scrip dividends may force the two banks to cut them to zero.

Cyclicals: Slower than expected economic growth globally could affect the bottom line of export-oriented cyclicals, which have so far largely escaped the impacts of the adverse European economy. However, we are seeing some negatives beginning to emerge, such as Daimler struggling to maintain its dividends.

Taking into account the risks and their strong rally recently, tactically, we believe there may be better entry points to go long dividends next year. In the trade idea section we also suggest ways to take advantage of the low implied volatility via dividend options.

We still prefer the front end (2013s – 2015s) to back end dividend futures as we believe the low growth environment benefits yield trades, whereas long dated dividends move more in line with equities. As growth continues to be sub-trend we see potential for short-dated dividends to outperform long-dated ones in 2013. We also continue to see more value in single stock dividend futures than the index dividend futures, due to the discount of the single stock to the index dividend futures.

y = 1.8427x - 29.715R² = 0.9112

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21



FTSE Dividends

We initiated our recommendation to go long FTSE dividends in March 2012, and we continue to favor FTSE dividends into next year. They offer similar upside potential to the Euro STOXX 50 dividends (Figure 40) but with lower risks. As shown in Figure 41, the biggest payers in the FTSE generally bear lower risks than those in the Euro STOXX 50.

Figure 40: FTSE divs still offer attractive upsides

Potential upsides to estimates


Figure 41: Biggest payers of FTSE 2014 dividends (JPM estimates)


Nikkei Dividends

The 13s have posted an impressive performance of over 21% this year, nearly double the performance of Nikkei 225. We believe the driver of this outperformance is not only due to investors’ search for yield but also the overall resilient guidance for March 2013 dividends—now nearly 90% guided—despite weaker than expected earnings (see Table 2). With upside to our bottom-up estimate standing at less than 4% for the 13s, we believe 14s have the most attractive risk/reward profile for the coming year (see Table 3).

Political tailwinds may also benefit Nikkei dividends as Shinzo Abe, the Liberal Democratic Party leader who is pro-inflation and pro-QE, looks likely to win the upcoming election. His unusually aggressive stance on pro-inflation—stating that the Bank of Japan should pursue unlimited easing to achieve a 2-3% inflation target—has helped drive the yen and Nikkei 225 to seven-month low and high, respectively. The end of deflation and achieving Abe’s inflation target may lead to EPS improvement, in particular for the upcoming FY ending March 2014, and hence benefit Nikkei dividends as well.

Table 2: Earnings summary for CY2012 Q3

EPS Sales

Beat 41.9% 16.3%

Hit 7.0% 47.6%

Missed 51.1% 36.1%Source: J.P. Morgan Equity Derivatives StrategyBased on TOPIX constituents that have announced earnings from Oct-Nov ’12.

Table 3: Bottom-up estimates, potential upside, and Sharpe Ratio

Source: J.P. Morgan Equity Derivatives Strategy*Potential upside is with respect to the offer side of the dividend swaps.

6%

17%

24%

6%

17%

25%

6%

15%

24%

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25%

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2013 2014 2015

Upside to IBES

Upside to Bbg Ests

Upside to JPM Ests

HSBA, 12%BP/, 8%

GSK, 7%

VOD, 6%

RDSA, 5%

BATS, 5%RDSB, 5%

AZN, 4%

Others, 48%

Maturity

JPM

Estimates

Current

Offer

Potential

Upside*

Potential

Upside (ann.)

90D Realized

Vol (ann.) Sharpe Ratio

2012 208.0 208.1 0.0% -0.1% 2.7% -0.03

2013 213.0 206.3 3.2% 2.4% 4.1% 0.59

2014 225.8 205.0 10.1% 4.2% 6.4% 0.66

2015 238.2 200.8 18.6% 5.2% 9.6% 0.55

2016 241.5 196.8 22.7% 4.8% 11.2% 0.43

2017 244.9 192.5 27.2% 4.6% 12.4% 0.37

2018 248.3 188.5 31.7% 4.4% 12.9% 0.34

2019 251.8 184.3 36.6% 4.3% 15.1% 0.29

2020 255.3 180.0 41.8% 4.3% 14.1% 0.30


22



H-shares/Hang Seng Dividends

H-shares 12s returned 21% over the past year while the underlying index eked out less than a 2% return. Due to its attractive upside potential, H-share dividend futures drew investors’ attention and the total traded value for the year increased significantly from USD 80mn to USD 430mn.

This year, H-shares/Hang Seng dividends overall do not appear as attractive as they were last year. Based on the bottom-up estimates from various sources, we see upside potential for H-shares of 0-4% in 13s and 9-14% in 14s, while we see potential upside for the Hang Seng of 4-7% in 13s and 11-16% in 14s. Taking these magnitudes of upside potential, liquidity (bid/ask spread) and uncertainties into account, we remain neutral on H-shares/Hang Seng dividends at this point.

Figure 42: H-shares Dividend (HSCEIDPI) Bottom-up Estimate


Figure 43: Hang Seng Dividend (HSIDPI) Bottom-up Estimate


S&P 500 Dividends

Concerns over the fiscal cliff have led the S&P 500 dividend term structure to flatten significantly since the US presidential election (Figure 44). This concern stems from changes in taxation should the cliff fail to be resolved favorably for dividends. Under existing law, the taxation of dividends reverts from a flat 15% rate in 2012 to being treated as ordinary income in 2013, and thus potentially being subject to a maximum federal tax rate of 43.4% (39.6% top bracket rate + 3.8% Affordable Care Act levy). Should this negative scenario materialize, where dividend tax rates rise significantly above those applied to long-term capital gains, we expect high yielding stocks to underperform and companies on aggregate to shift part of their shareholder remuneration policy from dividends to buybacks. In response to the cliff threat, a number of US companies paid special cash dividends in late 2012 (Costco, Las Vegas Sands, Wynn Resorts, Franklin Resources, etc.) or pulled forward part of their 2013 payout (Walmart, Oracle, DR Horton, General Dynamics, etc.). Due to the binary risk associated with the fiscal cliff, we currently hold a neutral view on S&P 500 dividends, expecting the term structure to flatten further if taxes rise to regular income levels, or steepen if they remain in line with long-term capital gains.

Figure 44: The S&P 500 dividend swap term structure has flattened significantly since the US elections


379 378 374

407

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326

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23



Derivatives Ideas for 2013

Volatility Trades

Relative Value Asia versus DM Volatility Spreads Remain Attractive

On the back of the policy actions from the ECB/Fed, which are perceived to have removed tail risks and provided a put option to the market, risk premia have contracted substantially. As equity volatility and skew drop to multi-year lows across the globe, Asia volatility continues to trade relatively cheap compared to volatility in the developed markets (DM). With robust structured product issuance activities, the volatility supply/demand imbalance continues to weigh heavily on Asian volatility markets, especially with lower market liquidity as well as the lower risk capacity for structured product dealers going into year-end. Hence, a number of interesting relative value opportunities, such as going long Asia volatility versus going short SPX, UKX, or AS51 volatility, remain attractive going into 2013.

Although we do not expect any imminent catalyst for the structural dynamics of Asia volatility to change, the realized spreads are carrying positively against the implied levels, in particular for indices associated with active structured product markets such as HSCEI, KOSPI2, and NKY. Should there be another risk-off event, we would expect Asia volatility to react more violently than DM volatility, both on an implied and realized basis, similar to history. Hence, at this time, we continue to see value in going long Asia volatility through these indices versus going short DM volatility as the current depressedspread levels give investors long carry and volatility without being short tail risks. For trade implementation, we prefer using delta-hedged puts rather than variance swaps, in order to avoid the relatively rich Asian variance convexity while taking advantage of the wide gap in Asian vs. DM downside skews. Volatility pairs that stand out from this analysis include HSCEI, NKY, or the Asia Basket vs. SPX, HSCEI vs. UKX, and HSCEI vs. AS51.

Figure 45: Volatility spread of H-shares versus S&P 500


Figure 46: Volatility spread of Asia Basket versus S&P 500


Table 4: Indicative tradable levels and statistics of various Asia versus DM volatility spreads (Dec-13 maturity)

Source: J.P. Morgan Equity Derivatives Strategy. *Asia Basket is equally weighted basket of H-shares, KOSPI 200, and Nikkei 225.

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12M 90% Implied Volatility Spread

12M Realized Volatility Spread


Current Entry

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12M 90% Implied Volatility Spread12M Realized Volatility Spread


Current Entry

H-shares

vs S&P 500

KOSPI 200

vs S&P 500

Nikkei 225

vs S&P 500

Asia Basket

vs S&P 500*

H-shares

vs FTSE 100

KOSPI 200

vs FTSE 100

Nikkei 225

vs FTSE 100

H-shares

vs ASX 200

Nikkei 225

vs ASX 200

Dec-13 90% ATMF IV Spread 2.5% -1.8% -1.7% -0.3% 4.2% -0.1% 0.0% 6.7% 2.5%

Variance Spread over Put IV Spread 2.1% 1.7% 2.1% 2.0% 4.2% 3.8% 4.2% 3.8% 3.7%

Current 8.8% 4.3% 2.2% 5.1% 7.9% 3.4% 1.3% 9.6% 3.0%

Max 27.5% 7.7% 9.1% 13.2% 27.7% 6.8% 10.4% 30.8% 14.8%

Min 3.1% -4.3% -5.2% -0.3% 3.4% -2.9% -3.4% 5.3% -1.9%

Average 13.0% 1.2% 2.3% 5.5% 14.4% 2.5% 3.7% 16.2% 5.5%

3M RV Spread vs Put IV Spread (Carry) 4.7% 4.4% 5.5% 4.9% 2.5% 2.3% 3.4% 3.7% 4.5%

Put IV Spread %tile vs IV Spread 13.6% 42.2% 29.5% 25.4% 22.4% 63.2% 45.2% 22.8% 76.8%

Put IV Spread %tile vs RV Spread 0.0% 29.3% 9.8% 0.0% 5.0% 18.5% 11.0% 9.6% 29.5%

#REF! #REF! #REF! #REF! #REF!

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24



Go long 2014 Euro STOXX 50 dividend volatility

We recommend investors to go long 2014 Euro STOXX 50 dividend implied volatility as it appears attractive both on a stand-alone basis and compared to the Euro STOXX 50 equity implied volatility. Although we are positive on Euro STOXX 50 dividends, we also see the likelihood of a pickup in volatility early next year due to factors both specific to dividends (see Where we stand on the 2013 Euro STOXX dividends) and at a macro level (US fiscal cliff, Greek/Spanish situations).

The implied volatility on the 2014s is trading at an attractively low level. Figure 47 shows the ratio of Euro STOXX 50 dividend ATMF implied volatility to the cash index’s ATMF implied volatility as a function of the time to expiry for the dividend contract. Here we demonstrate that as a % of like-maturity Euro STOXX 50 equity implied volatility, the 2014s(52% of SX5E implied volatility) are significantly below both the 2012s’ (61%) and 2013s’ levels (73%) at the same point in their life. Additionally, the current implied volatility level also appears cheap compared to our expectations of what the 2014s are likely to realize for their remaining life, based on historical realized volatilities of past futures contracts. Investors can buy a 95 put on the 2014s as an overlay on a long futures position for 5.0 points (ref. 99.5). Although the initial premium appears high, investors would be able to monetize on a mark-to-market basis should a sell-off happen prior to its pull-to-realized.

Furthermore, given our aforementioned comparison between dividend volatility and equity volatility, investors can play the relative value and buy DEDZ4 95 strike puts (5% OTM) at 5.0%, funded by selling Dec 13 SX5E 2300 strike puts (~12% OTM) at 5.1% for a small credit. In addition to taking advantage of the negative convexity of dividends (downside beta greater than upside beta), the trade also provides a 7% margin of safety on the short Euro STOXX 50 put leg (Figure 48). The Dec-13 expiry is preferred, in our view, as beyond this date, the dividends are driven more by the pull to realized effect and tend to de-correlate from equities.

Figure 47: 2014 dividend implied volatility trading significantly below 2012s and 13s as % of Euro STOXX 50 volatility

Div ATMF vol as % of SX5E ATMF vol

Years to Expiry .


Figure 48: Selling Euro STOXX 50 2300 puts provide 7% margin of safety vs. buying DEDZ4 95 puts

SX5E Px DEDZ4 Px


Exploit Volatility Spillover and Clustering to Improve Carry Strategies

Many investors looking for yield believe there are currently opportunities in equity volatility carry. However, investorslooking to exploit volatility carry are faced with a dilemma in that they capture potentially large premia in good times but a likelihood of large losses when volatility spikes. While spikes are not easily predictable, in our paper Risk Premia in Volatility Markets: Exploiting Volatility Spillover and Clustering, we find that we can enhance the performance of volatility carry strategies and mitigate draw-downs from volatility spikes by exploiting two characteristics of volatility:

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https://mm.jpmorgan.com/EmailPubServlet?h=-2s2dbt6&doc=GPS-999930-0.pdf



25



Clustering (or persistency)—Whenever volatility is above (below) average it is more likely that volatility will remain higher (lower) than average.

Spillover—After an increase in volatility in one particular market, it is more likely that volatility will remain higher than average in related markets.

Our strategy that selects in which market to go short volatility and whether to go short, based on an econometric model that forecasts the probability of a positive risk premium, outperformed simply being short S&P 500 volatility by nearly 5% annualized since 2001 (Figure 49). The latest parameters for the selected model are shown in Table 5,11 where we apply a VAR approach12 to the volatility premium in the US, Europe, and Japan in order to derive a trading strategy. With this model in hand, our selected strategy applies the following modifications to a traditional short volatility strategy:

Frequent monitoring and trading: Instead of trading once a month and praying for nothing to happen over the next 30 days as in the case of a single variance swap, we use overlapping positions, trading a fraction of the notional invested every day (this enhancement is also incorporated into the benchmark in Figure 49).

Conditional on the expected premium: We only go short volatility at any day if the probability of a positive realized premium is high, as losses can be large. If over the next 30 days the probability of a positive premium according to our model is >85%, we go short volatility, if the probability is <65% we go long volatility, and we do nothing if the expected probability is 65-85%.

Figure 49: Exploiting Persistence and Spillover in Equities Markets

Excess return index

Source: J.P. Morgan, Bloomberg. Calculations are net of transaction costs and based on the model (described above) that trades US, Europe, or Japan variance swaps based on the probabilities of a positive premium. Probabilities are based on a limited dependent variable model where the probability of a positive premium depends on past values of realized and implied volatility in all the markets. The benchmark shown is always short S&P 500 volatility with daily overlapping variance swaps.

Table 5: Forecasting Volatility Premium—Selected ModelRegression coefficients and t-stats, constants are not reported

Source: J.P. Morgan, Bloomberg. Premium is measured as the difference between implied volatility at the beginning of the period and the average squared daily returns over the next month. Regressors are based on the monthly average of the implied volatility and range volatility computed using 10 business days.

See the report for more details on the model and methodology as well alternative implementations.

11 Our trading strategy actually re-estimates these equations every day, using only previous data.12 VAR (Vector Autoregression) is a statistical model used to capture the linear interdependencies among multiple time series, where the evolution of each series depends on the past realizations of the same variable and other variables in the system. We use VAR(1) here, implying that only one lag is used.

80

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Strategy

Benchmark

US(t) Europe(t) Japan(t)

Daily

US(t-1) 0.42 0.51 0.44

(t-stat) 2.57 5.45 1.52

Europe(t-1) 0.18 0.08 0.11

(t-stat) 1.80 0.97 0.88

Japan(t-1) 0.04 -0.09 0.25

(t-stat) 0.33 -1.56 1.31

R-sqr 0.12 0.14 0.14

Monthly

US(t-1) 0.59 0.93 0.40

(t-stat) 3.26 6.04 1.83

Europe(t-1) 0.19 -0.04 0.01

(t-stat) 1.30 -0.36 0.07

Japan(t-1) -0.06 -0.26 0.36

(t-stat) -0.41 -2.11 2.06

R-sqr 0.13 0.23 0.13


26



Option Strategies to Take Advantage of Flat Skews

As we noted in the previous section, implied skews have come down significantly in 2H12, especially in some Asian indices. The suppressed levels of skew, coupled with low volatility, make some long skew strategies attractive. Table 6summarizes the list of option strategies to take advantage of flat skews and indicative options prices.

For bullish strategies using vanilla options, investors can consider call spreads or call ratios to take advantage of rich upside skew. For instance, HSCEI 6M 105%-115% call spreads and 6M 1x2 105%-115% call ratios (buying one 105% call and selling two 115% calls) would cost 2.34% and 0.86% respectively, providing 39% and 77% savings vs. outright 105% calls (3.82% premium). NKY follows with the second highest savings of 33% and 65% for the same call spreads and call ratio structures, respectively. Given the breakeven levels vs. historical index range (Figure 51), NKY 1x2 105%-115% call ratios look appealing for investors chasing further upside in Japanese equities. Strategies involving selling upside volatility and skew through barriers, such as buying knock-out calls, appear attractive at current levels. For example, 6M ATM calls with a 115% knock-out barrier cost less than half of the equivalent vanilla puts in HSCEI, NKY and KOSPI 200.

For bearish strategies, we like risk reversals, which involve selling OTM calls to fund puts, as an effective strategy to extract value from the volatility curve. To buy 6M 90%-110% risk reversals, investors pay nothing for KOSPI 200 and even receive a small net credit for HSCEI. A short put ratio strategy also provides a handsome credit upfront due to low downside skews while providing protection against large market corrections. This strategy is suitable for investors who believe that the market is likely to remain range-bound but who want to hedge against a potential market crash scenario, asthe strategy would do well on MTM being long volatility and long skew. Investors can receive over 2% by shorting 6M 1x2 95%-85% put ratios in SX5E, HSCEI and NKY.

Table 6: Indicative pricings for various short skew strategies (for 6M tenors)

Source: J.P. Morgan Equity Derivatives Strategy. * Knock-in and knock-out occur based on daily observation at the close.

Figure 50: 6M 90-110% skew spread for major global indicesSkew Spread 5Y Percentile


Figure 51:NKY 6M 105%-115% 1x2 call ratio strike and breakevensIndex Level


SPX SX5E UKX DAX SMI NKY AS51 KOSPI2 HSI HSCEI

Bull Strategies

105%-115% Call Spread Long 1x105%C + Short 1x115%C 1.80% 1.78% 1.21% 2.35% 0.59% 1.93% 1.24% 2.10% 1.84% 2.34%

Savings vs Long 105% Call -7% -19% -6% -16% -3% -33% -9% -28% -26% -39%

105%-115% 1x2 Call Ratio Long 1x105%C + Short 2x115%C 1.67% 1.37% 1.13% 1.91% 0.57% 1.00% 1.12% 1.29% 1.18% 0.86%

Savings vs Long 105% Call -13% -37% -12% -32% -7% -65% -18% -56% -53% -77%

100% Call with 115% KO* Long 3.73% 2.33% 3.08% 3.33% 2.20% 1.99% 3.02% 2.29% 2.49% 1.85%

Savings vs Long 100% Call -11% -42% -6% -35% 7% -57% -10% -54% -43% -68%

100% Call with 115% KO w/ Full Rebate* Long 3.91% 2.69% 3.18% 3.79% 2.22% 2.42% 3.14% 2.69% 2.95% 2.45%

Savings vs Long 100% Call -6% -34% -3% -26% 8% -48% -7% -46% -33% -58%

Bear Strategies

90%-110% Collar Long 1x90%P + Short 1x110%C 1.48% 1.89% 1.44% 0.77% 1.20% 0.26% 0.72% -0.01% 0.45% -0.08%

Savings vs Long 90% Put -27% -34% -19% -61% -8% -86% -36% -101% -74% -104%

95%-85% Put Ratio Short 1x95%P + Long 2x85%P -1.79% -2.55% -1.63% -1.83% -1.66% -2.09% -1.23% -1.78% -1.95% -2.32%

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27



Dispersion Opportunities

FTSE – TOP 20 (ex RB/ LN) – Skew Spread: While several European index skews have reached record lows (e.g.,SX5E), FTSE skew continues to be a suitable selling candidate. We have seen FTSE 6M skew significantly rebound from its lows recently, even as implied volatility came down across indices and other asset classes. The difference between FTSE index skew and the skew of its constituents is highlighted in a previous report.

The absence of Q3 negative surprises (ex BG/ LN) brought single-stock implied volatility and skew down. The Barclaysheadlines surrounding its Dec-13 warrant sale further enhanced the trend. We have seen significant size of downside volatility being sold in Jun-13 and Dec-13 maturities. Other single names also had large down moves in the 6M 90-100%skew over the past two weeks: VOD LN -0.60%, BP/ LN -0.50%, BG/ LN -0.50%, ULVR LN -0.50%, RDSA and RDSB -0.40% and TSCO -0.30%.

Figure 52: There is a significant discrepancy between the FTSE Index

skew and the skew of its constituents


Figure 53: The spread between FTSE single stocks and index at 90% strikes looks attractive


We suggest buying FTSE Top 20 single name (ex RB/ LN) Jun-13 90% strike options versus short FTSE Index Jun-13 90% strike options. On the downside, we would be looking to reverse the trade if/when the carry of the spread disappears. The volatility spread entry level of 4.8% represents, in our view, a good level versus the recent 6M realized level of ~6.3% (Figure 53). The entry level looks interesting also when compared with a longer history as it is only 1 vol point away form the 5Y low.

AS51: Within Asia, although implied correlation levels have come down significantly, we prefer going long ASX 200 dispersion through buying single-stock Jun-13 90% options versus selling the index Jun-13 90% options. This trading strategy takes advantage of the cheap single-stock volatility and skew relative to the index, which is a result of heavy single-stock overwriting activities from investors searching for yield and index protection demand from investors using ASX 200as a proxy hedge to both developed markets and China, with lower volatility. The current indicative level of the Jun-13 90% top 15 single-stock versus ASX 200 option spread is at 4.7% (see Figure 54) versus the recent 6M realized spread of 6.0%. Relative to the 5Y realized spread history, the implied level is at the 20th percentile. In terms of implied correlation, the volatility spread represents a level of 55.5%. Although the volatility spread and correlation levels are not at the extremes,performance will likely be driven by sector rotation as capital flows from unattractive sectors (such as the defensives, which look quite fully valued) to more attractive sectors, hence driving sector and stock dispersions and supporting a lower correlation environment, in our view.

6M 90-100% SkewCurrent

Skew Level 5Y History %ile

2w absolute

skew change

UKX Index 4.3% 62% 0.2%

VOD LN Equity 1.9% 9% -0.6%

BP/ LN Equity 2.2% 18% -0.5%

BG/ LN Equity 0.5% 1% -0.8%

BARC LN Equity 1.7% 0% -1.0%

ULVR LN Equity 1.6% 1% -0.3%

TSCO LN Equity 1.6% 4% -0.3%

6M Realised Vol Spread

Actual Implied vol Spread Level

4.00%

4.50%

5.00%

5.50%

6.00%

6.50%

Jun-12 Jul-12 Aug-12 Sep-12 Oct-12


28



Figure 54: AS51 6M Top 15 90% stocks to index implied volatility spread vs. realized historyVolatility Spread


0%

5%

10%

15%

20%

25%

Dec-07 Dec-08 Dec-09 Dec-10 Dec-11 Dec-12


Jun13 90% Straddle Volatility Spread (Top 15 vs AS51)

29



Macro/Directional Trades

Long Euro STOXX 50 Jun-13 call spreads funded by selling Jun-13 S&P 500 call spreads

In their 2013 Outlook, JPM European Equity Strategists Matejka and Cau expect Eurozone equities to continue to outperform the US. In our strategists’ view, the source of risks appears to be shifting. In a sense, the Eurozone is more advanced in the adjustment process, and fiscal drag will likely be greater in the US in 2013. Meanwhile, Eurozone earnings and margins have already repriced lower, and Eurozone valuations still look extremely cheap when contrasted with their UScounterparts, at more than a 40% P/B and cycle-adjusted P/E discount. Accordingly, we recommend buying Euro STOXX 50 Jun-13 100-110% call spreads funded by selling S&P 500 Jun-13 100-110% call spreads for an overall credit of 0.3% of notional, to play our strategists’ view and take advantage of the skew differential between the two indices. The structure additionally buys the implied volatility spread between the Euro STOXX 50 and S&P 500 at ~2.2%, while the most recent 6M realized volatility spread between the two indices was ~7.8%.

We choose a 6M tenor for the structure as this expiry fits well with the time horizon of our strategists’ view and works well from a skew standpoint. Euro STOXX 50 implied volatility remains higher than that of the S&P 500 index, and the volatility spread between the two indices widens as maturity increases. Therefore, an outright call switch is less attractive (Figure 55). On the other hand, the 6M call wing skew for the S&P 500 remains elevated, especially compared to that of the Euro STOXX 50 index (Figure 56), allowing investors to achieve favorable pricing in the call spread switch.

Figure 55: Euro STOXX 50 implied volatility is higher than that of the S&P 500, making an outright call switch less attractiveEuro STOXX 50 and S&P 500 ATMF volatility and their spread


Figure 56: The Euro STOXX 50 6M upside skew has been declining throughout the year, while it has held firm for the S&P 500Euro STOXX 50 and S&P 500 6M ATM-110% skew


EM Asia versus US Outperformance Strategies

The recent improvement in China’s flash PMI provides more evidence to the view that the economic recovery is gaining traction, lending more support to our equity strategists’ regional current trade preference of OW in EM Asia versus the S&P 500. This trade is not merely tactical. We believe it is a longer term theme for 2013 justified by the growth and flow improvement in EM Asia and the fiscal cliff risks in the US. In terms of countries that are most attractive in Asia, our EM strategist has India as the top pick. India combines improving policy, easier monetary conditions, and pent-up investment demand with a market that generated EPS growth despite significant macro headwinds in 2012. Add to this a huge demographic dividend and an equity market with low exposure to government sponsored companies. The Philippines and Thailand are next. The Philippines stands out as a country with improving economic growth, with consumption picking up (same-store retail sales growth at 10%), along with a newfound investment up cycle. The pervasiveness of record-low interest rates is a key driver of these positive trends, with policy rates of 3.5% forecast to come off further in 1Q13. After growing below potential from 2004, Thailand is now enjoying a period of economic strength. Our Thailand OW is based on robust domestic demand, sustained low interest rates, undemanding valuations, and scope for positive EPS revisions.

10%

14%

18%

22%

1M 2M 3M 6M 9M 12M

SPX SX5E

2%

3%

4%

5%

Dec-10 Jun-11 Dec-11 Jun-12

SX5E 6M ATM - 110 skew

SPX 6M ATM-110 skew


30



To implement the EM Asia versus US outperformance view via options, call switch or outperformance option strategies can be used. In terms of underlyings, we can consider MSCI EM Asia (MXMS) for the long leg and S&P 500 (SPX) for the short leg. For the call switch strategy, investors are going long call options on MXMS while going short call options on SPX to implement the relative value trade on the upside only. For the outperformance option strategy, investors are going long an option that provides 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. In terms of country weighting, China is the largest country in EM Asia at 30%, while the countries with OW ratings—India, Philippines, and Thailand—have weightings of 11%, 4%, and 2%, respectively.

Table 7 summarizes the indicative option pricing and backtest results of 6M call switch and outperformance option strategies with different strikes. Since MXMS is a USD composite index, it provides full exposure to the equity markets in EM Asia as well as their currencies (versus USD), which tend to be highly correlated due to capital inflows during risk-on periods. 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. For investors who want further savings on option premium, the switch strategy with call spreads is also very attractive. Against the backdrop of our strategists’ relative view, the risk of SPX rallying and outperforming MXMS on the upside is small, in our view, especially when SPX has already outperformed MXMS greatly over the past two years.

Table 7: Indicative pricings and backtest results of various 6M MXMS vs. SPX option strategies for the past 10 yearsBased on 6M rolling returns


Figure 57: Rolling performance of various 6M MXMS vs. SPX option strategies for the past 10 yearsGross P&L at Maturity


Sell S&P 500 ratio risk reversals to exploit the structural mispricing of tail events

As discussed in the Outlook for Volatility section, S&P 500 upside options significantly under-price the probability of upside tail events while overpricing the downside compared to the long-term likelihood of such events. For example, the realized frequency of a 10% up move in six months is ~2 times more likely than options imply, while the realized frequency of a 10% down move in 6M is less than half as likely as implied by options (Figure 14). Although skew on the S&P 500 has flattened materially over the last six months, it remains the steepest among global indices and remains steep relative to the levels of implied volatility. For example, the ratio of 6M 90-110% skew to ATM implied volatility, and the ratio of 90% strike volatility to 110% strike implied volatility are both elevated relative to history (both at their ~85th percentile relative to the last five years of data, Figure 58).

Accordingly, we recommend selling levered risk reversals on the S&P 500 to exploit the continued mispricing of tail events. Investors can currently buy 2.8x 6M 110% strike calls vs. selling 1x 90% strike puts on the S&P 500 at zero cost (indicative), giving a levered upside exposure. For example, these risk reversals could be overlaid to an underweight equity

ATM Call

Switch

105% Call

Switch

105% - 120%

Call Spread

Switch

6M ATM

Outperf

Option

6M 105%

Outperf

Option

Avg Return 6.1% 5.9% 2.9% 7.6% 5.1%

Avg Gains 13.4% 13.4% 7.9% 13.2% 11.3%

Avg Losses -4.5% -4.3% -4.2% N/A N/A

Max Return 53.6% 52.7% 15.0% 53.6% 48.6%

Min Return -19.0% -15.6% -15.0% 0.0% 0.0%

% Occur Gain 53.1% 48.8% 44.3% 57.6% 44.7%

Option Premium 0.75% 0.90% 0.65% 4.90% 2.80%

-20%

-10%

0%

10%

20%

30%

40%

50%

60%


ATM Call Switch

105% Call Switch

105% - 120% Call Spread Switch

6M 105% Outperformance

31



position to permit investors to quickly pick up delta in case of a rally. This leverage ratio is attractive relative to history, in its 97th percentile compared to the last 10 years of data (Figure 59).

Figure 58: S&P 500 skew remains steep relative to implied vol levels, giving attractive leverage on risk reversals


Figure 59: S&P 500 6M 90-110% risk reversal gives high leverage relative to historyRatio of 6M 110% call to 90% put in a costless risk reversal


Buy calls on MSCI Mexico for cheap exposure to our EM Strategists’ favored market

Mexico is one of our EM Equity Strategy team’s top picks for 2013 (see Latam Year Ahead 2013). They see limited downside to earnings estimates, supported by strong macro, with room for an upside surprise due to structural reforms of labor, fiscal, and energy policies. Further, consumer demand is expected to remain strong, fueled by credit growth. The Mexican peso is one of our FX strategists’ favorite Latam currencies for 2013, and they expect it to appreciate ~5% vs. the USD by mid 2013. This would provide a further boost to the EWW, which is priced in USD.

Mexico, however, was one of the top performing emerging markets in 2012 and has relatively expensive valuation, while delays to the anticipated structural reforms could cause its market to de-rate. As a result, we prefer to play the market through options rather than delta-1 in order to limit downside risks. EWW implied volatilities are currently at 5+ year lows (Figure 60), pulled down by the subdued realized volatility this year, while upside skew is relatively steep (6M ATM-110% skew is in its 76th percentile over the last five years). This makes OTM calls relatively attractive in our view, despite their recent negative carry. For example, 6M 105% calls are currently indicated at ~3.1% of notional.

Figure 60: EWW implied vol is at 5+ year lows, while Mexico is one of our EM Strategists’ favorite markets for 2013


0%

10%

20%

30%

40%

50%

60%

100%

110%

120%

130%

140%

150%

160%

170%

180%

2009 2010 2011 2012

Ratio of 90%/110% strike 6M implied vol

6M 90-110% Skew / ATM (right)

0.5

1.0

1.5

2.0

2.5

3.0

3.5

2001 2003 2005 2007 2009 2011

10%

20%

30%

40%

50%

60%

70%

80%

2008 2009 2010 2011 2012

6M ATM implied volatility


32



Call switch to play long Turkey / short South Africa

In the context of a positive 2013 outlook for the CEEMEA region in the CEEMEA Year Ahead by JPM Strategist Aserkoff, Turkey continues to be our key Overweight for four reasons: 1) accelerating GDP and EPS growth; 2) reasonable valuations; 3) improving current account deficit; and 4) it has a more positive macro outlook than the rest of CEEMEA. On the other hand, South Africa is the key Underweight due to our cautious outlook on the mining sector given weak commodity prices and the labor strife.

In terms of volatility, South Africa’s Top40 implied volatility ranks as one of the richest across global indices, based on its implied to EWMA realized volatility spread (Figure 61), whereas Turkey’s ISE30 (XU030) appears less expensive. Therefore, we favor going long ISE30 calls and short Top40 calls to play the relative value in implied volatility. Additionally, the Top40 index is heavily overweight materials companies compared to the MSCI South Africa, a more widely followed index (Figure 62). Therefore, our cautious stance on the mining companies can be better expressed via the Top40 index. A 6M 105% call switch (long ISE30 vs. short Top40) costs indicatively 0.82%.

Figure 61: Top40 implied vol among the richest across global indices6M ATM implied less EWMA realised volatility spread across sector indices


Figure 62: Top40 sector weights vs. MSCI South Africa

% index weight


In addition, FX also plays an important role when investing in the two indices. As Figure 63 shows, in USD terms, the Top40 index behaves differently from its ZAR version. The effect is less pronounced for ISE30. Our strategists expect the ZAR weakness to continue until mining output and exports pick up (mid Q1 seems likely). Investors can be protected from the FX effect by entering into a call switch struck in USD: a 6M 105% call switch between ISE30 and Top40 struck in USD can be entered for an indicative credit of 0.3%.

Figure 63: Top40 YTD performance in local currency and USD


Figure 64: ISE30 YTD performance in local currency and USD


-3%

2%

7%

EW

WE

EM

TO

P4

0E

WZ

SP

XR

DX

US

DN

KY

DA

XO

MX

HS

IX

U03

0S

X5E

AE

XU

KX

HS

CE

IS

MI

CA

CIB

EX

FTS

EM

IB

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35%

C. D

isc

C. S

tapl

es

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erg

y

Fin

anci

als

Hea

lth

Ca

re

Ind

ust

rials

Ma

teria

ls

Tel

eco

m

TOP40 MSCI SA

90%

95%

100%

105%

110%

115%

120%

Jan Apr Jul Oct

ZAR denom.

USD denom.

90%

110%

130%

150%

170%

Jan Apr Jul Oct

TRY denom.

USD denom.


33



Maintain Cautiously Bullish Stance on Nikkei Dividend SteepenersWe have highlighted previously that EUR/JPY appears to be a good indicator of risk-on sentiment in Japan, and Nikkei dividend steepeners historically have tracked it closely (see Figure 65). Shinzo Abe, the current favored candidate for Japan Prime minister, has been touting a pro-inflation stance that has already weakened the yen to a seven-month low. Furthermore, recent Eurozone talks on saving Greece have led to EUR/USD strengthening back up to the 1.3 level after plunging below 1.21 in July as Spanish regions sought out aid from the central government. The weakening yen and the strengthening euro have led to EUR/JPY rising above 107, a level not seen since April. We believe Nikkei dividend steepeners may benefit as the yen weakens against the euro on monetary policies in Japan and an improving macroeconomic environment in the Eurozone.

Figure 65: Historical performance of steepener spreads and comparison to EUR/JPY for the past two years


We have compared the performance of various steepeners since they hit their widest on July 24. The analysis suggests that steepeners with 14s as the short leg have lagged other pairs, and hence pairs of 14/19, 14/18, 14/17, and 14/16 look the most attractive for potential tightening in the coming months (see Table 8). Our most preferred pair, 14/19, has tightened from -45.0 pts on July 24 to -21.3 pts in the course of four months. However, given the move on EUR/JPY, we believe the 14/19 spread can narrow further to as tight as -13.2 pts, based on our regression (see Figure 66). As steepeners have posted impressive performance over the past month on talks of the potential election of pro-QE Shinzo Abe, we may see a pullback going into year-end. However, any pullback is an opportunity to buy on a dip, in our view, as steepeners are poised to benefit from political tailwind and potentially improving market sentiment at year-start.

Table 8: Performance of Nikkei dividend steepeners since hitting their YTD widest on July 24

Steepener Pair

As of Jul 24, ‘12

As of Nov 26, ‘12

Change (div pt)

Change (abs %)

14/19 -45.0 -21.3 23.8 53%14/18 -38.0 -17.0 21.0 55%14/17 -30.5 -12.8 17.8 58%14/16 -21.5 -8.5 13.0 60%13/19 -58.5 -22.5 36.0 62%12/18 -56.1 -20.8 35.4 63%14/15 -11.5 -4.3 7.3 63%13/18 -51.5 -18.3 33.3 65%


Figure 66: Regression of 1M change of 14/19 steepener vs EUR/JPY

Source: J.P. Morgan Equity Derivatives Strategy. Data since Jan ’11.

90

95

100

105

110

115

120

125

-60

-50

-40

-30

-20

-10

0Nov-10 Feb-11 May-11 Aug-11 Nov-11 Feb-12 May-12 Aug-12 Nov-12

EUR

/JPY

Nik

kei d

ivid

end

stee

pen

er (d

iv p

ts)

2013/2017 steepener 2013/2018 steepener

2013/2019 steepener 2014/2018 steepener

2014/2019 steepener EUR/JPY

As EUR/JPY recovered from the lowest level since 2000, Nikkei dividend steepener spreads all narrowed substantially.

y = 0.6763x - 0.4456R² = 0.3012

-15

-10

-5

0

5

10

15

-10 -5 0 5 10

1M c

hg o

f 14/

19 s

teep

ener

1M chg of EUR/JPY

34



Downside Protection Trades

Identifying Cheapest Index Put Hedges

In this section, we attempt to identify 3M 95% puts on major global indices that are most cost efficient, by looking at how the indices have performed historically during market downturns. With a market correction defined as when MSCI AC World (MXWD) falls more than 5% within a three-month period, we calculate the median returns of all the indices over the same three-month periods for the past five years and compare them with the current 3M 95% put option prices. Through this analysis, we have found:

In terms of absolute premium levels (row 2 in Table 9), SMI puts currently have the lowest absolute premium level,closely followed by AS51 and NIFTY, all being less than 1.0%.

Out of 1,795 three-month rolling returns, there were 585 data points with MXWD falling more than 5%. In such occasions, indices such as FTSEMIB, HSCEI, RDXUSD, and CECEEUR fell most sharply with the median loss greater than 16%. On the other end of the spectrum, indices such NDX, NIFTY, XU030, DJI, and SPX posted less than 9.5% median losses (Figure 67).

In terms of the median return on put premium, SMI, AS51, AEX, HSI, TWSE, and HSCEI seem to be the most attractive as their 3M 95% puts would have provided greater than 5.0x median returns on the premium. On the other hand, for US indices (such as NDX, INDU, RTY, SPX), XU030, and MSCI Mexico, put prices seem to be least justified with the median 3M return on put premium being less than 1.8x.

Figure 67: Median return of global indices when MXWD has fallen more than 5% over 3 months3M Median Return % of Times

Source: J.P. Morgan Equity Derivatives Strategy. *Based on 3M rolling returns for the past 5Y.

Figure 68: 3M 95% put premium and median return on premium under the scenario of MXWD falling more than 5%Median Return on Premium

3M 95% put premium Source: J.P. Morgan Equity Derivatives Strategy. *Based on 3M rolling returns for the past 5Y.

Table 9: Indicative 3M 95% put premium and potential return on put premium during the market downturns (MXWD falling more than 5%)

Source: J.P. Morgan Equity Derivatives Strategy * (3) Median 3M return with MXWD falling >5%: median of 3m rolling returns when MXWD fell more than 5% over the past 5 years. (5) Median 3M 95% put return on premium = {ABS(Median 3M Return w/ MXWD Falling > 5%) -5% - (3M 95% Put Premium)}/ (3M 95% Put Premium)

60%

70%

80%

90%

100%-20%

-15%

-10%

-5%

0%

FT

SE

MIB

HS

CE

IR

DX

US

DC

EC

EE

UR

IBE

XM

SC

I Bra

zil

AE

XS

X5E

WIG

20T

WS

EC

AC

HS

IO

MX

KO

SP

I2N

KY

DA

XA

S51

RT

YM

SC

I Mex

ico

SM

IU

KX

SP

XIN

DU

XU

030

NIF

TY

ND

X

Median Loss (LHS, reversed)

% of Data w/ 3M Return <-5% (RHS)SMI

AS51TWSE

HSI

AEX

HSCEI

WIG20

OMXFTSEMIB

CECEEUR

KOSPI2

DAX

CACSX5E

NKY

UKXNIFTY IBEXRDXUSD

RTY

INDU

SPX

EWZ

EWW

XU030NDX

0.0X

1.0X

2.0X

3.0X

4.0X

5.0X

6.0X

7.0X

0.0% 0.8% 1.6% 2.4% 3.2%

0

SMI AS51 NIFTY UKX HSI TWSE OMX AEX INDU KOSPI2 DAX SPX NKY CAC NDX SX5E HSCEI XU030 FTSEM

IB

RTY MSCI

Mexico

CECEE

UR

MSCI

Brazil

IBEX RDXU

SD

(1) 3M 95% Put Implied

Volatility

12.7% 13.1% 15.9% 14.8% 16.5% 15.5% 17.1% 16.1% 16.0% 16.8% 18.1% 17.2% 18.2% 18.8% 19.1% 19.3% 20.3% 21.0% 21.1% 20.5% 20.5% 22.2% 23.6% 22.4% 27.0%

(2) 3M 95% Put Premium 0.76% 0.84% 0.96% 1.23% 1.29% 1.32% 1.36% 1.37% 1.41% 1.47% 1.55% 1.59% 1.62% 1.80% 1.84% 1.87% 1.89% 1.90% 2.06% 2.13% 2.30% 2.31% 2.54% 2.71% 3.11%

(3) Median 3M Return w/

MXWD Falling >5%

-10.5% -11.0% -8.6% -9.9% -13.7% -13.9% -12.9% -14.5% -8.7% -12.5% -12.0% -9.4% -12.1% -13.8% -7.8% -14.3% -16.9% -8.6% -17.1% -10.9% -10.7% -16.0% -14.7% -15.5% -16.7%

(4) % of Times of 3M 95%

Put Being ITM

82% 87% 64% 88% 88% 76% 73% 88% 79% 75% 84% 85% 88% 96% 63% 96% 85% 62% 99% 76% 79% 91% 78% 96% 84%

(5) Median 3M 95% Put

Return on Premium

6.2X 6.0X 2.7X 3.0X 5.7X 5.8X 4.8X 5.9X 1.6X 4.1X 3.5X 1.8X 3.4X 3.9X 0.5X 4.0X 5.3X 0.9X 4.8X 1.8X 1.5X 3.8X 2.8X 2.9X 2.8X

Cheap premium Rich premium

35



Buy Jan VIX calls spread funded by selling Jan puts

As discussed in the Outlook for Volatility section, the current level of VIX looks cheap relative to virtually every macroeconomic indicator across the globe. All 81 US macro series indicate that the VIX should be ~7.2 points higher on average. In addition, it is not clear how the US fiscal cliff will be resolved, but we do know that it can have significant implications on equity markets and indirectly on the VIX. In our view, the risk for market volatility is skewed to the upside.

In light of this view, we recommend buying the Jan 2013 17-22 VIX call spreads and selling the 16 strike put to fund it partially as an inexpensive hedge against lawmakers’ failure to agree to a fiscal cliff solution. This trade can be entered into for a net cost of ~$0.30. The maximum profit on the trade is 4.7 vegas. Investors would realize the maximum profit if at expiry VIX opens above 22. The investor would lose one for one below 16 owing to the short put leg. But it must be noted that over the past five years VIX has opened below 16 only 7% of the time.

We back-tested this strategy since 2006 where the investor buys VIX ATM and ATM+5 call spreads and funds it by selling a put with a strike that would make the trade as close to cashless as possible. Note that obtaining exactly cashless is difficult as we back-tested with listed options. In Figure 69 below we show the average profit-loss of this strategy by the level of VIX at inception. For example, an investor who would have entered into this strategy when VIX was between 20 and 22 would have lost on average -3.5 vegas historically.

We believe that the current level of the VIX makes this trade attractive. It can be seen from Figure 69 that an investor entering into this trade when the VIX is between 14 and 16 would make on average 1.8 vegas. The maximum profit would have been 3.1 vegas in July 2007 when VIX was 16. In order to determine which strikes are optimal for the call spread we back tested ATM – ATM+5, ATM+1 – ATM+6, and ATM+2 – ATM+7 call spreads and found that the ATM – ATM+5 call spread has the highest average profit when VIX is between 14 and 16 at trade inception. In terms of the maturity, we like the second month better than the front month as an investor entering into a similar strategy with second month maturity when VIX is between 14 and 16 would have made ~1.8 vegas on average vs. 0.1 vegas for the front month maturity.

Additionally, the current steep VIX upside skew makes call spreads attractive relative to outright calls as the 2M 25-50 delta VIX skew is in its 97th percentile relative to the last five years of data.

Figure 69: Back-test results of rolling VIX call spreads and funding it by selling put. Horizontal axis shows the VIX level at inception Vega Profit/Loss


Figure 70: VIX call skew is near record steepness, cheapening VIX call spreads significantly vs. outright calls2M 25-50 delta VIX call skew


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36



Japan “Armageddon” Put – Buy 1Y 90% Nikkei 225 Put Contingent on 10Y JPY Swap Rate

As the world’s third largest economy, Japan remains an economic powerhouse that can influence the global economy and its growth outlook. However, Japan’s debt-to-GDP ratio remains one of the highest in the world (Figure 71), and its trade deficit may continue to deteriorate on the back of a struggling economy and shrinking population. Furthermore, the outstanding amount of JGBs continues to grow, and next year over ¥216trn of bonds are expected to mature. If the trade deficit continues to worsen, the nation may have to depend on foreign investors for funding—today, ~91% is funded domestically.

While we are not bearish on Japan, investors who are looking to hedge tail risk for Japanese equities may consider an equity put contingent on rates rising to take advantage of the current level of cross-asset correlation. Specifically, we recommend a 1Y 90% Nikkei 225 put option contingent on 10Y JPY swap rate (JYISDP10) above 1.2% at maturity, indicatively available for 0.40%, which is a ~90% discount compared to a 1Y 90% vanilla put (3.9% prem). The 10Y JPY swap rate is currently at a multi-year low of 0.68%, with the five-year average standing at ~1.26% (above the contingent strike level) and rose as high as ~2.15% in mid 2008.

Figure 71: Global comparison of debt-to-GDP ratio (2011 est.)Debt-to-GDP Ratio

Source: J.P. Morgan Equity Derivatives Strategy, Central Intelligence Agency.

Figure 72: FTSE/GBP correlation has been well supported during 2012, but we see signs of it breaking down6M Correlation between FTSE 100 & GBP


British Protection—Buy 95% UKX and 102.50% GBPUSD Jun-13 Dual Digital @ 10%

If UKX index performance is below 95% at maturity and GBPUSD performance is above 102.50 %, the structure will pay10 times the premium invested. We are suggesting the structure for several reasons:

Our equity strategist, Mislav Matejka, remains cautious on the outlook for UK equities, and the JPM GDP forecast for 2013 was reduced by 0.50% recently. Although one could argue that UK equities are not expensive, they are heavily weighted to Energy and Materials (30%), sectors that we believe will struggle into next year.

In the meantime, the GBP FX market should remain attractive relative to USD. For 2013, our Asset Allocation teambelieves there will be a major step-up in QE buying, mainly from the Fed ($1tr of bond purchases), and we don’t think the Bank of England will be sidelined. This would be supportive for the GBP versus USD. Furthermore, our FX Strategy team’s 2013 year-end target for GBP is 1.63.

The BOE’s actions in 2012 (i.e., additional QE) increased equity/FX correlation. We see this correlation softening in 2013. This trade idea takes advantage of the high level in implied correlation between UKX index and GBPUSD as the Dual Digital is net short correlation (Figure 72).

206%

165%

129%120% 118%

108% 108%

87% 86% 85% 81%69% 68%

44%

0%

50%

100%

150%

200%

250%

-20%

-10%

0%

10%

20%

30%

40%

50%

60%

70%

Jun06 Jun07 Jun08 Jun09 Jun10 Jun11 Jun12

UKX Index / GBPUSD Curncy

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Risks of Common Option Strategies

Risks to Strategies: Not all option strategies are suitable for investors; certain strategies may expose investors to significant potential losses. We have summarized the risks of selected derivative strategies. For additional risk information, please call your sales representative for a copy of “Characteristics and Risks of Standardized Options.” We advise investors to consult their tax advisors and legal counsel about the tax implications of these strategies. Please also refer to option risk disclosure documents.

Put Sale. Investors who sell put options will own the underlying stock if the stock price falls below the strike price of the put option. Investors, therefore, will be exposed to any decline in the stock price below the strike potentially to zero, andthey 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, upsidelosses 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 coveredcall 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 Delta One Strategy group. Views expressed may differ from the views of the research analysts covering stocks or sectors mentioned in this report. Structured securities, options, futures and other derivatives are complex instruments, may involve a high degree of risk, and may be appropriate investments only for sophisticated investors who are capable of understanding and assuming the risks involved. Because of the importance of tax considerations to many option transactions, the investor considering options should consult with his/her tax advisor as to how taxes affect the outcome of contemplated option transactions.

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.

Important Disclosures

Company-Specific Disclosures: Important disclosures, including price charts, are available for compendium reports and all J.P. Morgan–covered companies by visiting https://mm.jpmorgan.com/disclosures/company, calling 1-800-477-0406, or emailing [email protected] with your request.

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 28, 2012

Overweight(buy)

Neutral(hold)

Underweight(sell)

J.P. Morgan Global Equity Research Coverage 44% 44% 12%IB clients* 52% 46% 34%

JPMS Equity Research Coverage 42% 48% 10%IB clients* 69% 61% 53%

*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.

Equity Valuation and Risks: For valuation methodology and risks associated with covered companies or price targets for covered companies, please see the most recent company-specific research report at http://www.jpmorganmarkets.com , contact the primary analyst or your J.P. Morgan representative, or email [email protected].

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Registration of non-US Analysts: Unless otherwise noted, the non-US analysts listed on the front of this report are employees of non-US affiliates of JPMS, are not registered/qualified as research analysts under NASD/NYSE rules, may not be associated persons of JPMS, and may not be subject to FINRA Rule 2711 and NYSE Rule 472 restrictions on communications with covered companies, public appearances, and trading securities held by a research analyst account.

mailto:[email protected]

http://www.jpmorganmarkets.com/

mailto:[email protected]

https://mm.jpmorgan.com/disclosures/company

39



Conflict of Interest This research contains the views, opinions and recommendations of J.P. Morgan research analysts. J.P. Morgan has adopted research conflict of interest policies, including prohibitions on non-research personnel influencing the content of research. Research analysts still may speak to J.P. Morgan trading desk personnel in formulating views, opinions and recommendations. Trading desks may trade, or have traded, as principal on the basis of the research analysts’ views and research. Therefore, this research may not be independent from the proprietary interests of J.P. Morgan trading desks which may conflict with your interests. As a general matter, J.P. Morgan and/or its affiliates trade as principal in connection with making markets in fixed income securities, commodities and other investment instruments discussed in research reports.

Other Disclosures

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Options related research: If the information contained herein regards options related research, such information is available only to persons who have received the proper option risk disclosure documents. For a copy of the Option Clearing Corporation's Characteristics and Risks of Standardized Options, please contact your J.P. Morgan Representative or visit the OCC's website at http://www.optionsclearing.com/publications/risks/riskstoc.pdf

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http://www.optionsclearing.com/publications/risks/riskstoc.pdf

40



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