2018 Equity Volatility Outlook Not With a Bang, But a Whimper. Mandy Xu, Equity Derivatives Strategy

Transcription

1 2018 Equity Volatility Outlook Not With a Bang, But a Whimper Mandy Xu, Equity Derivatives Strategy

2 Executive Summary Low Vol to Continue: In our core scenario, we expect S&P to realize 9.5% for the year and a median VIX level of 12.5 (vs. 11 in 2017) Potential Volatility Shocks: From sharply higher interest rates (10Y above 3.5%) to a trade war (NAFTA/China), a number of tail events could drive the VIX to excess of 20 Vol Supply & Demand: We discuss investment trends in the derivatives market that can impact supply & demand for volatility from hedge funds, asset managers, insurance, pensions, and retail investors Correlation to Remain Muted: We expect slightly higher sector correlation but lower intrasector correlation in 2018 as earnings, M&A, and tax changes come into focus 2018 Themes & Trade Ideas Top Thematic Ideas: - Further upside in US equities: buy SPX call spread collar and timer calls - Monetize steep volatility term structure via selling forward variance - EEM outperformance still in mid-cycle - Financials: multiple tailwinds to buoy sector - Energy: play catch up rally - Yield enhancement via put selling - CS MATRIX: a building block approach to trend investing Macro/Tail Hedges: - Best-of put to hedge global equity sell-off - CS TOPS to play flight to safety - HYG put spread 2

3 2018 VIX Forecast

4 VIX Framework We decompose the VIX into 3 components: 1. Baseline volatility: our expectation for realized volatility driven by economic fundamentals 2. Skew: the excess premium due to the supply & demand for volatility as an asset class 3. Kurtosis: the excess premium volatility traders charge to account for tail risk Kurtosis Skew Our forecast: median VIX level of 12.5 for 2018 Forecast Min/Max: 8-25 Baseline Volatility 2017 median VIX level: 11.1 Min/Max Range: 9-16 Source: Credit Suisse Equity Derivatives Strategy 4

5 Establishing Baseline Volatility 2018 S&P Year-End Price Target: 3000 CS US Equity Strategy team is forecasting another strong year for the S&P, with a year-end target of 3000 (+12%) driven by: Supportive macro fundamentals: a global synchronized recovery, stable CPI, limited wage inflation, and little risk of recession Strong earnings growth: The team is forecasting 17% EPS growth in 2018, of which 5.2% is from topline revenue, 8.6% from expected tax benefits, and the rest from a combination of expanding margins and increased buybacks. This compares with 10.9% EPS growth in Despite rising multiples, we do not see current valuations (17.2x fwd EPS) as excessive (although certainly closer to the high end of their LT historical ranges). Moreover, while research has shown negative relationship between valuations and longer-term stock returns, we find no relationship over shorter periods such as 1-year (see below). Credit Suisse 2017 and 2018 Projected EPS Growth Breakdown % % % 10.9% 2016 EPS Rev Oper Margin Int & Tax Share Count Source: CS Equity Reseearch 2017 EPS Rev Oper Margin Int & Tax Share Count 2018 EPS 5

6 % of Time Observed Baseline Volatility Forecast Potential Paths to SPX 3000 (+12%) First, we forecast the expected volatility for S&P to get to 3000 (+12%) using a bootstrapped Monte-Carlo methodology. Given the skewness in the volatility distribution of sampled paths, we exclude cases where the S&P was bouncing back from a large correction (e.g. 1938, 2003, 2009) 2018 baseline volatility forecast = 9.5% Source: Credit Suisse Equity Derivatives Strategy Bootstrapped Monte-Carlo Methodology: Calculate forecasted S&P returns Calculate rolling 1-year historical returns for S&P from 1928-present Create distribution of returns by extracting every instance in which a 1Y price path results in a return equal to our forecasted S&P target return Calculate the realized volatility of each resulting instance Calculate the mean realized volatility in which the 1Y price path equals our S&P return target Baseline volatility=the mean of the sampled realized volatilities 35% 30% 25% 20% 15% 10% 5% Distribution of Sampled Volatilities Median=11.8 Min=5.2 Max=35.8 0% Volatility Ranges January

7 Structural Skew: Supply & Demand of Volatility Source: Credit Suisse Equity Derivatives Trading Source: Credit Suisse Equity Derivatives Trading 7

8 VIX vs. Subsequent Realized Derivatives Usage Trends Fundamental L-S Hedge Funds After a disappointing 2016, L/S hedge funds bounced back in 2017, up ~13% yoy (CS L/S Index) The positive performance was driven by: Crowding in Tech: Tech/Internet Retail accounted for 40-50% of net exposure among L/S funds. Even during the June correction, managers held onto their longs. Option usage was focused on levering upside exposure at the stock level, with some tactical hedging through QQQ puts. Extreme stock and sector dispersion: S&P intersector correlation fell to near all-time lows in December. Low correlation/high dispersion is positive for stock pickers (more idiosyncratic risk) We saw an aversion to hedging at the macro level and a focus on using SS options to lever directional views (esp using shorter-dated/weekly options) - both trends we expect to continue into 2018 given our forecast for continued low vol and low correlation. Volatility Hedge Funds Vol carry funds had another banner year with the VIX falling to all-time lows. The group was up 9.1% in 2017, as measured by the EurekaHedge CBOE Short Volatility Index Performance benefitted from the substantial impliedrealized volatility spread (avg 4.3 vol pts) with realized volatility falling to multi-decade lows (average 1M rlz=6%, low of 3%). See chart below. Vol-arb funds had a more challenging year, up just 3.3% in 2017 (Eurekahedge CBOE Relative Value Volatility Index). These funds typically have a long vol, long convexity bias, neither of which performed last year. Funds made money from US dispersion and from being opportunistic buyers of exotic var spreads (e.g. outperformance corridors, min/max, etc) PnL of a Systematic Short Vol Strategy Last Year 0-2 Jan-17 Mar-17 May-17 Jul-17 Sep-17 Nov-17 PnL VIX Subsequent 1M realized Source: CS Equity Derivatives 8

9 Derivatives Usage Trends US Pensions The funded status of both public and corporate pension plans improved in 2017 to 71.6% and 85.2%, respectively (source: Milliman). Corporate DB plans have continued to allocate away from equities (35%) toward fixed income (45%). In contrast, public pensions have largely held steady their asset allocation mix over the past 5 years, with equities remaining at ~50%. That said, we ve seen a shift within their equity exposure to more structurally defensive equity factors such as quality or low vol. Along with keeping their long equity exposure, we ve seen pensions adding tail risk overlays to their portfolio. Funds are still averse to paying premium for hedges so strategies that are low/minimal carry and long convexity (such as CS TOPS) have found the most traction. Given the persistently low yield environment, carry/risk premia strategies continue to be popular (e.g. systematic put selling, call overwriting, VIX roll down). We ve also seen pensions allocating capital for risk recycling portfolios generated by banks and other sources of unique return streams. In 2018, we expect the theme of inflation/higher rates to come into bigger focus Public Pensions Asset Allocation Steady Over Last 5 Years Source: Milliman Long Convexity/Low Carry Tail Strategies Gain in Popularity Source: Credit Suisse Equity Derivatives 9

10 Volatility (%) Derivatives Usage Trends Asset Managers Whereas a few years ago option usage by this community was centered around hedging (usually put spreads or put spread collars with very little vega footprint), asset managers are now using options primarily for: Levered delta exposure: throughout 2017, we ve seen persistent demand for upside S&P calls. This has kept S&P call-side skew extremely bid (1Y call skew currently at a 3Y high). 5.0% Yield enhancement: the bulk of this activity has been through either selling index puts outright or iron condors (call spreads and put spreads), typically 3-6 weeks in maturity. Lately, we ve seen more interest in selling extremely short-dated variance (uncapped, <2 weeks in tenor). This constant supply of short-dated volatility has helped keep S&P term structure extremely steep SPX Term Structure (1Y-1M) Insurance Once the dominant player in the long-dated (10Y) vol space, insurance companies have shifted their product mix in recent years to significantly reduce the duration of their vega exposure (<5Y). They have also become more tactical/dynamic through use of short-dated options (1-3M tenors), smart beta/qis overlays, and becoming more opportunistic and price sensitive (e.g. trading when there are axes). Recent conversations have focused on hedging tail risk (2008-type scenarios) in low premium structures (e.g. best-of puts, compound options) or protecting against an equity correction catalyzed by higher rates (e.g. hybrids). Vol Targeting ~33% of Risk Controlled AUM 0.0% -5.0% -10.0% 01-Jul-15 SPX Imp Vol Spd (1Y - 1M) Source: Credit Suisse Locus 31-Dec Jun Dec Jun-17 10

11 Issuance by Product Type (%) Derivatives Usage Trends Structured Products Issuance jumped 34% last year as the market rally led to more buybacks and call events. Interestingly, despite the strong equity market, investors continued to favor yield enhancement products now ~75% of our issuance over growth products also saw a rebound in international interest, with ~40% of our issuance having some sort of international underlying (including global baskets of SPX/RTY/SX5E) vs. just 19% in One of the clearest trend we ve seen is the shortening of tenors as the yield curve has flattened. Our notional weighted average tenor has dropped from a high of 3.6Y in 2015, to 3.4Y in 2016, to 2.5Y last year. With index volatility falling to record lows, interest in higher vol sectors has picked up accordingly, particularly in Tech and Energy. XOP issuance almost tripled in 2017 vs (XOP-SPX 1Y implied vol spread widened to as high as 19 vol pts). This retail XOP flow left a notable impact on the XOP term structure with bank exotic desks needing to sell long-dated vol as the sector sold off in 1H17. As a result, the back end of the vol curve flattened/inverted. This positive spot/vol correlation picked up again in Oct when the sector bounced back and dealers had to buy back some of their vega hedges. Yield Enhancement Issuance Up to 75% of Total 100% 90% 80% 70% 60% 50% 40% 30% 20% 10% 0% Source: CS Equity Derivatives Yield Enhancement Structured Products Access/ Group Growth Source: CS Equity Derivatives Desk XOP Vol Curve Impact From Exo Desk Hedging Source: CS Equity Derivatives Desk 11

12 Kurtosis: Potential Tail Catalysts Catalysts to watch for in 2018 that could drive the VIX higher: 1. Sharply higher bond yields: return of inflation, Fed surprise 2. Trade war: NAFTA exit, China sanctions 3. Geopolitical risks: North Korea, Iran, Russia investigation, etc 12

13 Catalyst #1: Bond Yields Sharply Higher 3.5%) CS Rates Strategy team forecasts 10Y to end 2018 at 2.9% vs. 2.4% in 2017 CS Global Equity Strategy team thinks the danger level for equities is 10Y at ~3.5%, at which point equities would no longer screen cheap against bonds In order to get such a rapid rise in yields, we would need to see a sharp acceleration in US wage inflation and a much more hawkish Fed 13

14 Change in VIX (Pts) Change in VIX (Pts) Change in VIX (Pts) Impact of Higher Rates on Equity Vol In general, there is zero empirical relationship between higher rates and higher VIX over the past 20 years (see below) Except when yields rise sharply in response to surprise Fed tightening Chg in 10Y Yield vs. Chg in VIX (1M) R 2 = Monthly Change in Yields (Net %) Chg in 10Y Yield vs. Chg in VIX (3M) R 2 = Monthly Change in Yields (Net %) Chg in 10Y Yield vs. Chg in VIX (6M) R 2 = Monthly Change in Yields (Net %) 14

15 VIX Index 10Y Yield (%) VIX Index 10Y Yield (%) When the Fed Surprises the Market 2013 Taper Tantrum: Bernanke s surprise taper comments in May 2013 led to almost 1pp increase in the 10Y yield, with the VIX surging 8 pts to a high of Tightening Cycle: Started with a surprise rate hike on Feb 4 th, followed by an intermeeting hike. The aggressive pace led to a bond market carnage (10Y yield +3 ppts that year) while equity volatility more than doubled from 10 to high of Taper Tantrum 1994 Tightening Cycle VIX Y Yield Taper Tantrum 1.5 Jan-13 Mar-13 May-13 Jul-13 Sep-13 Nov-13 Jan VIX 24 10Y Yield Surprise Rate Hike 8 Sep-93 Dec-93 Mar-94 Jun-94 Sep-94 Dec

16 Term Premium (%) What Will It Take This Time? Even though the Fed has said 2% inflation is a target, not a ceiling, recent history suggests otherwise (e.g. raising rates when inflation has persistently undershot 2%) FOMC board composition is also expected to be more hawkish in 2018 Markets currently pricing in very little risk of inflation If we get several higher than expected inflation readings, how will the Fed react? Trade rec: Buy HYG downside (see pg 42) 2 10Y Tsy Term Premium Rate Vol Near All Time Lows=Very Little Inflation Risk Priced In ACM 10Y Term Premium Jan-13 Jan-14 Jan-15 Jan-16 Jan-17 Jan Jul Dec Jun Dec Jun Dec-17 3M x 10Y Implied Vol (Left Axis) Historical Data: 3M x 2Y Implied Vol (Right Axis) Historical Data: 6M x 2Y Implied Vol (Right Axis) Historical Data: 6M x 10Y Implied Vol (Left Axis) Source: Credit Suisse Locus 16

17 EWW Vol (%) USDMNX Vol (%) Catalyst #2: Trade War NAFTA: March deadline looms with little progress, Mexico elections start in Spring China: trade penalties risk tit-for-tat retaliation leading to full-scale trade war EWW vs. USDMXN: implied vols have started rising in recent months on the possibility of US withdrawal from NAFTA, but risk premium still muted compared to US election No comparable risk premium priced into US equities (either S&P or single stock) EWW (Mexico Equity) vs. USDMXN Vol EWW 3M Imp Vol (LHS) 9 17 USDMXN 3M Imp Vol (RHS) Jan-16 May-16 Sep-16 Jan-17 May-17 Sep-17 Jan-18 Source: Eurasia Group 17

18 Catalyst #3: Geopolitical Risks 2018 catalysts to watch: North Korea: fire and fury, escalation of rhetoric/sanctions Middle East: Iran, Syria, Saudi Arabia > upside risk for oil prices United States: government shut down, Russia investigation Europe: Italian elections, Catalonia independence, etc Cyberattacks: from state and non-state actors See our recommended tail hedges (pg 30) 18

19 Ratio Impact on VIX and VVIX Geopolitical risk premium keeping vol-of-vol elevated > even as VIX fell to new all-time lows in 2H17, VVIX stayed above 90 (~70 th percentile high over last 10 years). Dislocation between VVIX and VIX suggest high jump risk in vol regime This is supported by the elevated VIX skew (2M 25D call/put skew in the 90 th percentile) We expect the VVIX/VIX divergence to continue in 2018 on sustained geopolitical risk VIX Index (LHS) VVIX Index (RHS) VVIX/VIX Ratio 6 60 Jan-17 Mar-17 May-17 Jul-17 Sep-17 Nov-17 Jan-18 0 Jan-07 Jan-09 Jan-11 Jan-13 Jan-15 Jan-17 19

20 Summary: 2018 VIX Forecast Steady-state forecast: if no major macro tail events occur and the current positive economic trends continue, we forecast a median VIX level of 12.5 for this year and a realized volatility of 9.5%. Potential volatility shocks: if any of the negative macro shocks we outlined earlier were to occur from sharply higher rates to trade wars to geopolitical shocks we estimate the VIX could trade in excess of 20. Vol spikes are likely to be short-lived (unless accompanied by a deterioration in the economic fundamentals) VIX Scenarios 20

21 Is Low Vol a Bubble?

22 Is Low Vol a Bubble? State of the World State of the Market VS 22

23 Fundamentals Trump Trump Synchronized global growth Accommodative central bank policy Zero signs of inflation Strong EPS growth (2/3 of S&P rally last year came from earnings) Extreme sector dispersion (partly driven by fiscal policy) Source: CS Equity Research Source: CS Equity Research 23

24 Volatility Was Low in in context: VIX hit all time low of 9.14 in Nov-17 and traded in an extremely tight range all year (min/max of 9-16) S&P realized volatility last year was 6.7%, making it the 2 nd least volatile year in history (record low was 5.1% in 1964) Median VIX vs. Min/Max Range 24

25 Ratio VIX vs. Subsequent Realized But NOT Cheap In fact, VIX traded on average 4.5 pts above 1M realized volatility last year The average implied/realized premium (~65%) was the largest on record going back to VIX inception Hence why vol selling was such a profitable trade, even with VIX at 9! High implied/realized spread suggest healthy risk premium priced into vol markets 1.7 Implied/Realized Vol Premium PnL of a Systematic Short Vol Strategy Last Year Average VIX/Realized Vol Premium Jan-17 Mar-17 May-17 Jul-17 Sep-17 Nov-17 PnL VIX Subsequent 1M realized 25

26 Median VIX Levels (Quarterly) Can Low Vol Be Sustained? Just how long can low vol go on for? The longest sustained low vol regime was from 4Q04 to 2Q06 where VIX averaged less than 14 for 11 consecutive quarters The current low vol regime just finished its 6 th consecutive quarter To get sustained high vol, you need a deterioration in the fundamental outlook (e.g. economic recession, sovereign debt crisis, etc) which we do not expect in VIX Regimes Since Inception 60 Low Vol (VIX<14) High Vol (VIX>24) Medium Vol (VIX 14-24) 11 consecutive quarters of low vol 6 consecutive quarters so far

27 Current Cycle May Be Even Longer Source: CS Equity Research Source: CS Equity Research 27

28 SPX Return Vol vs. Future Returns Does low volatility suggest complacency or higher risk of a future correction? Not really: no relationship between median VIX level and subsequent S&P returns In fact, S&P does worst during medium vol regimes (avg subsequent quarterly return of 0.9%) than in low vol (avg return 2.2%) or high vol regimes (avg return 5.8%) 25.0% VIX Level vs. Subsequent SPX Return (%) 20.0% 15.0% 10.0% 5.0% 0.0% -5.0% % -15.0% -20.0% -25.0% VIX Level 28

29 2018 Themes & Trade Ideas

30 2018 Themes & How to Play Them 1. Equity Rally to Continue, Volatility to Remain Low: SPX call spread collar for levered upside exposure at (almost) zero premium Rich implied-realized vol spread: buy SPX timer call Monetize steep term structure via selling forward variance 2. Low Correlation/High Dispersion: Sector dispersion: ideas in Financials and Energy Stock dispersion: sell rich single stock vol via put underwriting Regional dispersion: EEM/SPX outperformance; best-of put 3. Cheap Tail Hedges: Sharply higher rates: HYG downside protection Low carry & high convexity tail hedge overlay: CS TOPS Trend: CS MATRIX 30

31 Skew (%) Further Upside in US Equities With 17% forecast EPS growth in 2018 against a still constructive macro backdrop, we remain bullish on US equities, with a year-end target of 3000 on the S&P. Option market sentiment has turned extremely bullish, with S&P 1Y call skew hitting a 3-year high on elevated call demand. We like buying call spreads funded by selling a put as a low cost way to gain levered upside exposure while maintaining a downside buffer. Trade idea: Buy SPY Dec call spread funded by selling the 250 put, paying $0.83 in net premium, or 0.3% of spot (ref ). Upside participation starts from +4% until +13% while the downside put strike is 10% away. The trade has initial delta of 51 and a max payout ratio of 30x. ***The risk to buying a call spread collar is significant. S&P 1Y Call Skew -2.7 SPY 1Y Call-Side Skew (25D-50D) -2.8 Jan-17 Mar-17 May-17 Jul-17 Sep-17 Nov-17 Jan-18 Trade Payoff Diagram 31

32 Volatility (%) Realized Volatility to Remain Low Even though implied volatilities have fallen to near all-time lows (e.g. SPX 1Y ATM in the 5 th percentile low over past year), it still trades at almost double that of realized (13.0% vs. 6.7% realized), with the spread between the two in the 92 nd percentile high. Given the rich implied-realized spread, we like buying upside in S&P via timer options which removes this risk premium. Timer call provides leveraged upside exposure until the running realized variance exceeds a target variance or the expiry (whichever is sooner). Trade idea: consider buying the Dec 18 SPX ATM timer call with 8.5%^2 var budget for 3.95%. See below for other pricing iterations. For reference, the vanilla ATM call costs 5.2% (spot ref ) and you re buying implied vol at 13.1%. ***The risk to a timer call option is limited to the premium paid. 20.0% 17.5% 15.0% 12.5% 10.0% 7.5% 5.0% Dec-13 Dec-14 Dec-15 Dec-16 Dec-17 SPX 1Y ATM Implied Vol SPX 1Y Realized Vol Source: Credit Suisse Locus Dec 18 Timer Call Indicative Pricing Structure Expiry Strike Target Volatility Indicative Offer SPX Timer Call 21-Dec % 6.50% 3.18% SPX Timer Call 21-Dec % 7.50% 3.60% SPX Timer Call 21-Dec % 8.50% 3.95% SPX Timer Call 21-Dec % 9.50% 4.27% SPX Vanilla Call 21-Dec % 5.20% 32

33 Volatility Volatility (%) Monetize Steep Term Structure While short-dated implied vols are trading near record lows, there is still some premium left in longer-dated tenors (see chart below). As a result, term structure has steepened significantly to near all-time highs. We like selling forward variance as a way to monetize the steepness. In particular, we like selling the 18M/1Y part of the curve. Trade rec: Sell SPX Dec18/Jun19 forward starting variance at 18%, indicative offer (spot ref ). ***The risk to selling forward variance is potentially unlimited. 30% 25% SPX Volatility Term Structure 1.0% SPX 18M/1Y Vol Spread 20% 0.0% 15% -1.0% 10% 20Y min average 5% current 0% 1M 2M 3M 6M 1Y 2Y 3Y 5Y 7Y 10Y Tenor -2.0% -3.0% Dec-99 Dec-04 Dec-09 Dec-14 SPX Imp Vol Spd (18M - 1Y) Source: Credit Suisse Locus 33

34 EM Rally Still in Mid-Cycle Emerging Markets was the best performing region in 2017 (+35%), but the party may just be getting started. CS EM Equity Strategy team thinks we are only mid-cycle in the current bull phase for the asset class. Key reasons to be constructive include accelerating macro momentum (vs. DM), increasing profit margins, still reasonable valuations, positive earnings surprises, cheap EM FX, and fund flow momentum 34

35 EEM > SPX Outperformance Even though 2017 was a banner year for EEM, it has lagged SPX significantly since 2012, with the performance differential exceeding 90 ppts. The current rally has also lagged previous EM bull markets in terms of relative returns. Trade idea: Buy Dec 18 EEM>SPX 3% outperformance option for 3.3% of notional. The option pays out, at expiry, the excess difference in performance (EEM-SPX) over 3% (e.g. if EEM outperforms by 8%, the option pays out 5%). You can cheapen the option further by adding a condition that SPX has to be up at maturity, bringing total premium down to 2.0% of notional. ***The risk of buying an outperformance option is limited to the premium paid. EEM vs. SPX Performance Since Jan

36 Change in Correlation Sector Correlations Modestly Higher Inter-sector correlation fell to its lowest levels since the Tech Bubble in With no major fiscal policy on the agenda this year, we expect sector dispersion to normalize modestly from current extremes. Intra-sector correlations also fell significantly last year, particularly for the rate sensitive sectors such as XLU and XLP. With bond yields set to rise, we expect correlations for those sectors to be higher in 2018 while Financial sector correlation should decline. XLF realized correlation (1Y) screens the richest of all sectors, in the 67 th percentile. 5% Intra-Sector Realized Correlation (YoY Change) 0% -5% -10% -15% -20% Change (Corr Pts) -25% XLF XLK XLE XLB XLI XLV XLY XLP XLU 36

37 Top Sector Picks for 2018 CS US Equity Strategy team has the following GIC sector recommendations: Breaking it down further: Source: CS Equity Research 37

38 Skew (Ratio) Financials: KRE 1x2 Call Spread Both our US Equity Strategy team and our sector analysts are constructive on Financials given the backdrop of higher rates and deregulation, above average EPS growth, still reasonable valuations, and accelerating capital returns. Within this sector, we prefer Banks over Insurers & Diversified Fins. We like buying upside in KRE (Regional Banks) given its higher beta to interest rate moves and purer exposure to Banks vs. XLF (~50% weighting to Banks). With KRE already up 6% in the first two weeks, we like buying 1x2 call spreads to play for more moderated upside from here. The structure also takes advantage of the high call skew in KRE. Trade idea: Buy KRE Jun x2 call spread for $0.3 (spot ref 62.61) Upside participation starts +2.2% with max payout of $4 (13x) if KRE rallies 8.6% by expiry. You re not exposed to losses beyond premium paid until the sector has rallied more than 15% (above 72). ***The risk to buying a 1x2 call spread is potentially unlimited KRE Upside Skew in the 82 nd %tile High KRE 6M Call Skew (10D/40D) 0.86 Jan-17 Mar-17 May-17 Jul-17 Sep-17 Nov-17 Jan-18 Trade Payoff Diagram 38

39 Energy: XOP Catch-Up Rally XOP (E&P Sector) has lagged not just the broader market but also the recent oil rebound. WTI oil prices are now back to their highest level since Dec 2014 yet XOP is still down over 20% from then. CS Prime data shows that while managers have chased the rally in crude (net exposure at 98 th percentile high on a 3Y lookback), they ve yet to rotate into Energy stocks with net exposure remaining largely unchanged in recent weeks. If the back-end of the oil curve starts to move higher, we could see more rotation into the sector by long-only and L/S funds. Trade idea: For investors who want to add energy exposure but with limited risk, we like buying call spreads in XOP funded by selling a put. E.g. the Jun 18 35/41/45 call spread collar costs $0.35 (ref 39.72), with upside from +3% until +13% while the put strike provides a downside buffer of 12%. Trade has initial delta of 42 with max 11x leverage. ***The risk to buying a call spread collar is significant. $66.0 $64.0 $62.0 $60.0 $58.0 $56.0 $54.0 $52.0 Source: CS Derivatives Strategy WTI Futures Curve $50.0 FEB 18 MAY 18 AUG 18 NOV 18 MAR 19 JUN 19 SEP 19 DEC 19 Latest (Jan-12) A Month Ago (Dec-12) Source: CS Prime Risk Advisory 39

40 Low Correlation = Rich Single Stock Vol Low correlation environment signals investors are focused on single stock earnings and catalysts, with zero macro risk priced in Avg single stock 1M implied vol in the 60 th percentile high (over past 5 years) vs. index vol near all time low We like selling rich single stock vol selectively for yield enhancement Earnings Implied vs. Realized Moves in 2017 Sectors Avg. Implied Avg. Realized Avg. Spread Basic Materials 3.8% 3.4% 0.3% Communications 3.3% 3.9% -0.6% Consumer, Cyclical 4.5% 5.6% -1.2% Consumer, Non-cyclical 3.8% 3.7% 0.2% Energy 3.8% 2.9% 0.9% Financial 3.0% 2.2% 0.8% Industrial 3.9% 3.3% 0.6% Technology 3.6% 4.8% -1.3% Utilities 2.7% 1.2% 1.5% Total 3.6% 3.5% 0.1% Source: CS Equity Derivatives Trading 40% 35% 30% 25% 20% 15% 10% 5% 0% Oct-12 Oct-13 Oct-14 Oct-15 Oct-16 Oct Average SS 1M Implied Vol SPX 1M Implied Vol Ratio of SS vs. Index Vol 0.5 Oct-12 Oct-13 Oct-14 Oct-15 Oct-16 Oct-17 40

41 Sell Rich Single Stock Vol: Underwrite Puts Look for stocks that have a) underperformed in this rally, b) rich vol, c) constructive fundamentals, and d) attractive entry points if put the stock. The 18 names we ve identified have an average implied vol level of 23% (vs. VIX at 9) and an annualized yield of 10%. If put these stocks, you ll be buying at an effective price that is 3% above the 52-week low. ***The risk to selling puts is significant. 3M 95% Implied CS Research Put Premium Effective Buy Price (If Eff. Price as % From 52W Low Ticker Sector Total Stock Percentile Share Price Annual Effective Open Int Price Vol (1Y) Momentum Rating (% Spot) Premium Put Stock) Discount EXPE Consumer Discretionary 195, O 3.3% 13.0% % 5% BBBY Consumer Discretionary 123, N 5.5% 22.1% % 7% WHR Consumer Discretionary 51, N 2.9% 11.6% % 0% KO Consumer Staples 858, O 1.1% 4.3% % 8% CVS Consumer Staples 366, O 2.6% 10.4% % 10% PM Consumer Staples 214, N 1.8% 7.2% % 8% K Consumer Staples 95, N 2.1% 8.3% % 2% GIS Consumer Staples 194, N 1.9% 7.7% % 8% TAP Consumer Staples 42, N 2.2% 8.7% % 3% KMI Energy 653, O 2.7% 10.9% % 8% AIG Financials 395, O 1.9% 7.5% % -2% MRK Health Care 634, O 1.8% 7.2% % 2% CELG Health Care 537, O 3.2% 12.9% % 3% AGN Health Care 332, O 3.4% 13.6% % 1% SYMC Information Technology 205, O 3.3% 13.2% % 3% SO Utilities 132, N 1.5% 6.1% % -6% EXC Utilities 103, O 2.0% 7.8% % 7% DUK Utilities 86, N 1.3% 5.1% % -3% Average % 9.9% -7.5% 3.6% 41

42 Higher Rate/Lower Equity: HYG Downside Hedge High yield credit (HYG) serves as a good hedge in cases of both sharply lower equities (risk off) and sharply higher rates (hawkish Fed surprise) 100% 80% 60% HYG Correlation to Equities vs. Rates During the 2013 taper tantrum, HYG fell 7.5% in a month after 10Y spiked 100bps to 2.6%. In that same time period, SPX fell 5.8%. In times of economic distress/uncertainty, HYG follows equities lower. E.g. in 2011 during the US double dip recession scare, HYG fell 12% while SPX dropped 18% from July to September. CS Global Equity Strategy team thinks credit is more vulnerable to a correction in 2018 vs. equities on valuation, leverage, and default concerns. They note that credit spreads have widened on average 7 months before an equity market peak and preceded 8 of the last 9 market peaks. Currently, HYG implied vol still screens cheap though downside skew is extremely steep. We like buying put spreads in this environment. 40% 20% 0% -20% -40% -60% Taper Tantrum HYG-10Y Corr (3M Rolling) HYG-SPX Corr (3M Rolling) -80% Apr-11 Apr-12 Apr-13 Apr-14 Apr-15 Apr-16 Apr-17 HYG Hedge Idea Buy HYG Jul 18 80/85 put spread for $1.0 premium (spot ref 87.58). HYG 6M put skew (25D/50D) is in the 87 th percentile high Downside protection starts 2.9% lower until down 8.7%, while risk is limited to the premium paid. Trade has initial delta of 29 and a max payout ratio of 5x 42

43 Best-of Put to Hedge Global Sell-Off Not only have implied volatilities fallen to near record lows across global equity markets, but correlations have also broken down. Currently, realized correlation between SPX, IWM, EEM, and EFA has fallen to near a 10-year low of 65%. In market downturns, that correlation typically spikes to 90% (reached as high as 94% during the 08 and 11 crises). For investors concerned about a macro-driven correlated sell-off in global equities, we like buying best-of puts to take advantage of the near record low volatility and correlation environment we re currently in. 100% 90% 80% 70% 60% 50% 40% 30% 20% 10% Correlation Btw Global Equity Markets ~10Y Low 6M Realized Correlation Btw SPX, IWM, EEM, EFA 0% Jan-08 Jan-10 Jan-12 Jan-14 Jan-16 Jan-18 Put Premium Cost Comparisons (Dec 18 90% Individual vs. Basket Puts) Trade idea: Buy the Dec 18 90% strike bestof put on SPX, IWM, EEM, EFA for just 1.3% premium. The best-of put offers 40-70% discount to both the individual puts and the basket put (see table). ***The risk to buying a best-of put is limited to the premium paid. 43

44 CS TOPS: Low Carry/High Convexity Tail Hedge CS Tail Risk Overlay Protection Strategy (CS TOPS): seeks to capture market tail events by strategically allocating to long rates instruments Rationale: investors tend to gravitate to rates instruments during periods of market stress (flight-tosafety scenario), creating upward price momentum which, when captured, can help mitigate tail risk Methodology: CS TOPS trades US and euro zone bond futures with tenors ranging from 3M to 10Y when the model detects upward momentum in these futures The strategy exhibits very low cost of carry (e.g. down 2% in 2017 in a banner year for risky assets) and high convexity in true tail scenarios (e.g. it was up over 45% during the Global Financial Crisis and up 10% during the 2011 Eur Sovereign Debt Crisis). Please contact the CS Derivatives desk for details (Bloomberg ticker: CSTSERUS Index) Source: Credit Suisse, Bloomberg. All figures based on data from 31 Mar 00 to 31 Oct 17. Past performance not an indicator of future performance 44

45 CS MATRIX: Building Block Approach to Trend CS Multi-Asset Trend-Following Index ( MATRIX ) suite of indices provide investors with a simple and transparent framework to gain exposure to Trend/Momentum risk premia in a flexible and cost-efficient manner. MATRIX allows access to trend investing at all levels (single futures > single asset class > multi asset) with significant customization for investors. Please contact the CS Derivatives desk for details. Source: Credit Suisse Equity Derivatives 45

46 CS Equity Derivatives Monthly Macro Call Equity Derivatives Monthly Macro Trader Index Call: Next one on Thursday, January18, :15 AM NY TIME Each month, Credit Suisse ETF and Equity Derivatives Index team will host a call to discuss flows, positioning, and themes going into expiration. This month s call will focus on our outlook for volatility and best trade ideas for Host: Neerav Jain, Equity Derivatives Sales Speakers: Mandy Xu, Equity Derivatives Strategy Josh Lukeman, Delta 1 Trading Leo Mayer, Head of US Equity Derivatives Index Trading Mel Arslan, VIX Trading Dan Cohen, Head of European Index Flow Trading 46

47 Market Commentary Disclaimer Please follow the attached hyperlink to an important disclosure: Structured securities, derivatives and options are complex instruments that are not suitable for every investor, 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. Supporting documentation for any claims, comparisons, recommendations, statistics or other technical data will be supplied upon request. Any trade information is preliminary and not intended as an official transaction confirmation. Use the following links to read the Options Clearing Corporation's disclosure document: 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 options transactions. This material has been prepared by individual traders or sales personnel of Credit Suisse and its affiliates ('CS') and not by the CS research department. It is not investment research or a research recommendation, as it does not constitute substantive research or analysis. It is provided for informational purposes, is intended for your use only and does not constitute an invitation or offer to subscribe for or purchase any of the products or services mentioned. The information provided is not intended to provide a sufficient basis on which to make an investment decision. It is intended only to provide observations and views of individual traders or sales personnel, which may be different from, or inconsistent with, the observations and views of CS research department analysts, other CS traders or sales personnel, or the proprietary positions of CS. Observations and views expressed herein may be changed by the trader or sales personnel at any time without notice. Trade report information is preliminary and subject to our formal written confirmation. CS may, from time to time, participate or invest in transactions with issuers of securities that participate in the markets referred to herein, perform services for or solicit business from such issuers, and/or have a position or effect transactions in the securities or derivatives thereof. The most recent CS research on any company mentioned is at Backtested, hypothetical or simulated performance results have inherent limitations. Simulated results are achieved by the retroactive application of a backtested model itself designed with the benefit of hindsight. The backtesting of performance differs from the actual account performance because the investment strategy may be adjusted at any time, for any reason and can continue to be changed until desired or better performance results are achieved. Alternative modeling techniques or assumptions might produce significantly different results and prove to be more appropriate. Past hypothetical backtest results are neither an indicator nor a guarantee of future returns. Actual results will vary from the analysis. Past performance should not be taken as an indication or guarantee of future performance, and no representation or warranty, expressed or implied is made regarding future performance. The information set forth above has been obtained from or based upon sources believed by the trader or sales personnel to be reliable, but each of the trader or sales personnel and CS does not represent or warrant its accuracy or completeness and is not responsible for losses or damages arising out of errors, omissions or changes in market factors. This material does not purport to contain all of the information that an interested party may desire and, in fact, provides only a limited view of a particular market. 47