not with a bang, but a whimper - credit suisse

2018 Equity Volatility Outlook

Not With a Bang, But a Whimper

Mandy Xu, Equity Derivatives Strategy

Executive Summary

2

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 intra-

sector 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

January 2018 For Institutional Clients Only

2018 VIX Forecast

3 January 2018 For Institutional Clients Only

VIX Framework

Source: Credit Suisse Equity Derivatives Strategy

Baseline Volatility

Skew

Kurtosis

Our forecast: median VIX

level of 12.5 for 2018

Forecast Min/Max: 8-25

2017 median VIX level: 11.1 Min/Max Range: 9-16

January 2018 For Institutional Clients Only 4

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

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 2017.

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).

119

132

155

5.2%

4.7-0.3 1.1

5.2%

3.5

6.8

1.9

2016

EPS

Rev Oper

Margin

Int &

Tax

Share

Count

2017

EPS

Rev Oper

Margin

Int &

Tax

Share

Count

2018

EPS

10.9%

17.4%

Credit Suisse 2017 and 2018 Projected EPS Growth Breakdown

Source: CS Equity Reseearch

0%

5%

10%

15%

20%

25%

30%

35%

5-8 8-11 11-14 14-17 17-20 20-23 23-26 26+

% o

f Ti

me

Ob

serv

ed

Volatility Ranges

Distribution of Sampled Volatilities

Median=11.8 Min=5.2

Max=35.8

Baseline Volatility Forecast

January 2017

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

Source: Credit Suisse Equity Derivatives Strategy

For Institutional Clients Only 6

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%

January 2018

Source: CS Equity Derivatives Strategy

7

Structural Skew: Supply & Demand of Volatility


Source: Credit Suisse Equity Derivatives Trading

Source: Credit Suisse Equity Derivatives Trading

8

Derivatives Usage Trends

Fundamental L-S Hedge Funds Volatility 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 inter-sector 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.

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 implied-

realized 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).

Source: CS Equity Derivatives January 2018 For Institutional Clients Only

-2

0

2

4

6

8

10

12

14

16

18

Jan-17 Mar-17 May-17 Jul-17 Sep-17 Nov-17

VIX

vs. S

ubse

quen

t Rea

lized

PnL of a Systematic Short Vol Strategy Last Year

PnL VIX Subsequent 1M realized

Source: CS Equity Derivatives Strategy Source: CS Equity Derivatives Strategy

9


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

Source: Milliman


Source: Credit Suisse Equity Derivatives

Long Convexity/Low Carry Tail Strategies Gain in Popularity

Public Pensions’ Asset Allocation Steady Over Last 5 Years

10


Asset Managers Insurance

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).

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

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


01-Jul-15 31-Dec-15 30-Jun-16 30-Dec-16 30-Jun-17

-10.0%

-5.0%

0.0%

5.0%

Vo

latilit

y (

%)

SPX Imp Vol Spd (1Y - 1M)

Source: Credit Suisse Locus

SPX Term Structure (1Y-1M)

11


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.

2017 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 2016. 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. 2016 (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.

XOP Vol Curve Impact From Exo Desk Hedging

Yield Enhancement Issuance Up to 75% of Total

Source: CS Equity Derivatives Structured Products Group


0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

2013 2014 2015 2016 2017

Issu

an

ce b

y P

rod

uct

Typ

e (

%)

Yield Enhancement Access/ Growth

Source: CS Equity Derivatives Desk

Source: CS Equity Derivatives Desk

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


13

Catalyst #1: Bond Yields Sharply Higher (10Y @ 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


14

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)

-20

-15

-10

-5

0

5

10

15

20

25

-1 -0.5 0 0.5 1

Ch

ange

in V

IX (

Pts

)

Monthly Change in Yields (Net %)

R2 = 0.02

-30

-20

-10

0

10

20

30

40

-1 -0.5 0 0.5 1

Ch

ange

in V

IX (

Pts

)



R2 = 0.01

-30

-20

-10

0

10

20

30

40

-1 -0.5 0 0.5 1C

han

ge in

VIX

(P

ts)



R2 = 0


15

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 21.

1994 Tightening Cycle: Started with a surprise rate hike on Feb 4th, followed by an inter-

meeting 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 24


1.5

1.7

1.9

2.1

2.3

2.5

2.7

2.9

3.1

3.3

10

12

14

16

18

20

22

24

Jan-13 Mar-13 May-13 Jul-13 Sep-13 Nov-13 Jan-14

10

Y Y

ield

(%

)

VIX

Ind

ex

VIX

10Y Yield

Taper Tantrum5

5.5

6

6.5

7

7.5

8

8.5

8

10

12

14

16

18

20

22

24

26

Sep-93 Dec-93 Mar-94 Jun-94 Sep-94 Dec-94

10

Y Y

ield

(%

)

VIX

Ind

ex

VIX

10Y Yield

Surprise Rate Hike

2013 Taper Tantrum 1994 Tightening Cycle


16

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)


-1

-0.5

0

0.5

1

1.5

2

Jan-13 Jan-14 Jan-15 Jan-16 Jan-17 Jan-18

Term

Pre

miu

m (

%)

10Y Tsy Term Premium

ACM 10Y Term Premium

01-Jul-15 31-Dec-15 30-Jun-16 30-Dec-16 30-Jun-17 30-Dec-17

60

70

80

90

40

50

60

70

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

Rate Vol Near All Time Lows=Very Little Inflation Risk Priced In


17

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)

Source: Eurasia Group


5

7

9

11

13

15

17

19

21

23

15

17

19

21

23

25

27

29

31

33

Jan-16 May-16 Sep-16 Jan-17 May-17 Sep-17 Jan-18

USD

MN

X V

ol (

%)

EWW

Vo

l (%

)

EWW 3M Imp Vol (LHS)

USDMXN 3M Imp Vol (RHS)


EWW (Mexico Equity) vs. USDMXN Vol

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)


19

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 (~70th 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 90th percentile)

We expect the VVIX/VIX divergence to continue in 2018 on sustained geopolitical risk


60

70

80

90

100

110

120

130

140

6

8

10

12

14

16

18

20

22

24


VIX Index (LHS)

VVIX Index (RHS)

0

2

4

6

8

10

12


Ra

tio

VVIX/VIX Ratio


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

Is Low Vol a Bubble?


22

Is Low Vol a Bubble?



State of the World

VS

State of the Market

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


24

Volatility Was Low in 2017…



2017 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 2nd least volatile year in history

(record low was 5.1% in 1964)


Median VIX vs. Min/Max Range

25

…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

-2

0

2

4

6

8

10

12

14

16

18

Jan-17 Mar-17 May-17 Jul-17 Sep-17 Nov-17

VIX

vs.

Su

bse

qu

en

t R

ea

lize

d

PnL of a Systematic Short Vol Strategy Last Year

PnL VIX Subsequent 1M realized


0.8

0.9

1.0

1.1

1.2

1.3

1.4

1.5

1.6

1.7

1990 1993 1996 1999 2002 2005 2008 2011 2014 2017

Rat

io

Implied/Realized Vol Premium

Average VIX/Realized Vol Premium

0

10

20

30

40

50

60

70

1990 1993 1996 1999 2002 2005 2008 2011 2014 2017

Me

dia

n V

IX L

eve

ls (

Qu

arte

rly)

Low Vol (VIX<14)

High Vol (VIX>24)

Medium Vol (VIX 14-24)11 consecutive

quarters of low vol

26

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 6th 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 2018

6 consecutive

quarters so far

VIX Regimes Since Inception

27

Current Cycle May Be Even Longer




-25.0%

-20.0%

-15.0%

-10.0%

-5.0%

0.0%

5.0%

10.0%

15.0%

20.0%

25.0%

0 10 20 30 40 50 60 70

SPX

Re

turn

VIX Level

VIX Level vs. Subsequent SPX Return (%)

28

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%)

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


-2.8

-2.7

-2.6

-2.5

-2.4

-2.3

-2.2

-2.1

-2

-1.9


Skew

(%

)

SPY 1Y Call-Side Skew (25D-50D)

31

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’18 290-315 call spread funded by selling the 250 put, paying

$0.83 in net premium, or 0.3% of spot (ref 277.92). 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 Trade Payoff Diagram


32

Realized Volatility to Remain Low

Even though implied volatilities have fallen to near all-time lows (e.g. SPX 1Y ATM in the 5th

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 92nd 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 2767.56) and you’re buying implied vol at 13.1%. ***The risk to a timer call option is limited to the premium paid.


Dec-13 Dec-14 Dec-15 Dec-16 Dec-175.0%

7.5%

10.0%

12.5%

15.0%

17.5%

20.0%

Vo

lati

lity

(%

)

SPX 1Y ATM Implied Vol SPX 1Y Realized VolSource: Credit Suisse Locus

Dec’18 “Timer” Call Indicative Pricing


Structure Expiry StrikeTarget

Volatility

Indicative

Offer

SPX Timer Call 21-Dec-18 100% 6.50% 3.18%




SPX Vanilla Call 21-Dec-18 100% 5.20%

33

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 2786.24). ***The risk to selling forward variance is potentially unlimited.



0%

5%

10%

15%

20%

25%

30%

1M 2M 3M 6M 1Y 2Y 3Y 5Y 7Y 10Y

Vo

lati

lity

Tenor

SPX Volatility Term Structure

20Y min

average

current

Dec-99 Dec-04 Dec-09 Dec-14

-3.0%

-2.0%

-1.0%

0.0%

1.0%

Vo

lati

lity

(%

)

SPX Imp Vol Spd (18M - 1Y)Source: Credit Suisse Locus

SPX 18M/1Y Vol Spread

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


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 2008


36

Sector Correlations Modestly Higher

Inter-sector correlation fell to its lowest levels since the Tech Bubble in 2017. 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 67th percentile.



-25%

-20%

-15%

-10%

-5%

0%

5%

XLF XLK XLE XLB XLI XLV XLY XLP XLU

Ch

ange

in C

orr

ela

tio

n

Change (Corr Pts)

Intra-Sector Realized Correlation (YoY Change)


37

Top Sector Picks for 2018

CS US Equity Strategy team has the following GIC sector recommendations:

Breaking it down further:



38

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’18 64-68 1x2 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


0.86

0.88

0.9

0.92

0.94

0.96

0.98


Skew

(R

atio

)

KRE 6M Call Skew (10D/40D)

KRE Upside Skew in the 82nd %tile High

Trade Payoff Diagram


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 98th

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.


Source: CS Derivatives Strategy

WTI Futures Curve

$50.0

$52.0

$54.0

$56.0

$58.0

$60.0

$62.0

$64.0

$66.0

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

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 60th

percentile high (over past 5 years) vs. index vol near all time low

We like selling rich single stock vol selectively

for yield enhancement


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%

Earnings Implied vs. Realized Moves in 2017

Source: CS Equity Derivatives Trading

0%

5%

10%

15%

20%

25%

30%

35%

40%

Oct-12 Oct-13 Oct-14 Oct-15 Oct-16 Oct-17

Average SS 1M Implied Vol

SPX 1M Implied Vol

0.5

1.0

1.5

2.0

2.5

3.0

3.5

Oct-12 Oct-13 Oct-14 Oct-15 Oct-16 Oct-17

Ratio of SS vs.Index Vol



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.



Ticker SectorTotal

Open Int

Stock

Price

3M 95%

Implied

Vol

Percentile

(1Y)

Share Price

Momentum

CS

Research

Rating

Put

Premium

(% Spot)

Annual

Premium

Effective

Buy Price (If

Put Stock)

Effective

Discount

Eff. Price as

% From 52W

Low

EXPE Consumer Discretionary 195,944 132.36 28.19 66 -26.2 O 3.3% 13.0% 121.43 -8.3% 5%

BBBY Consumer Discretionary 123,857 22.82 39.73 82 -34.3 N 5.5% 22.1% 20.42 -10.5% 7%

WHR Consumer Discretionary 51,223 172.75 25.46 53 -21.2 N 2.9% 11.6% 159.11 -7.9% 0%

KO Consumer Staples 858,127 46.15 14.45 82 -7.9 O 1.1% 4.3% 43.35 -6.1% 8%

CVS Consumer Staples 366,853 78.78 23.82 73 -14.9 O 2.6% 10.4% 72.79 -7.6% 10%

PM Consumer Staples 214,294 104.5 18.59 55 -20.2 N 1.8% 7.2% 97.38 -6.8% 8%

K Consumer Staples 95,976 64.69 20.41 78 -11.5 N 2.1% 8.3% 60.12 -7.1% 2%

GIS Consumer Staples 194,896 57.85 19.51 61 -3.7 N 1.9% 7.7% 53.85 -6.9% 8%

TAP Consumer Staples 42,653 84.88 21.58 57 -14.7 N 2.2% 8.7% 78.80 -7.2% 3%

KMI Energy 653,001 19.52 24.51 75 -13.0 O 2.7% 10.9% 18.01 -7.7% 8%

AIG Financials 395,602 60.97 19.75 51 -14.9 O 1.9% 7.5% 56.79 -6.9% -2%

MRK Health Care 634,582 58.66 18.83 57 -20.5 O 1.8% 7.2% 54.68 -6.8% 2%

CELG Health Care 537,292 106 28.41 80 -27.5 O 3.2% 12.9% 97.29 -8.2% 3%

AGN Health Care 332,763 176.05 28.71 78 -37.4 O 3.4% 13.6% 161.25 -8.4% 1%

SYMC Information Technology 205,642 28.82 28.34 76 -10.4 O 3.3% 13.2% 26.43 -8.3% 3%

SO Utilities 132,235 44.84 16.40 93 -11.1 N 1.5% 6.1% 41.92 -6.5% -6%

EXC Utilities 103,832 38.39 19.75 70 -2.9 O 2.0% 7.8% 35.72 -7.0% 7%

DUK Utilities 86,176 78.9 15.15 57 -11.3 N 1.3% 5.1% 73.96 -6.3% -3%

Average 23 69 2.5% 9.9% -7.5% 3.6%

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)

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.


HYG Correlation to Equities vs. Rates

-80%

-60%

-40%

-20%

0%

20%

40%

60%

80%

100%

Apr-11 Apr-12 Apr-13 Apr-14 Apr-15 Apr-16 Apr-17

HYG-10Y Corr (3M Rolling) HYG-SPX Corr (3M Rolling)

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 87th 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

Taper Tantrum


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.

Trade idea: Buy the Dec’18 90% strike “best-

of” 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.


Correlation Btw Global Equity Markets ~10Y Low

Put Premium Cost Comparisons (Dec’18 90%

Individual vs. Basket Puts)



0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%


6M Realized Correlation BtwSPX, IWM, EEM, EFA

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-to-

safety 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

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

CS Equity Derivatives Monthly Macro Call


Equity Derivatives Monthly Macro Trader Index Call: Next one on Thursday, January18, 2018

8:15 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 2018.

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

Market Commentary Disclaimer

Please follow the attached hyperlink to an important disclosure: http://www.credit-suisse.com/legal_terms/market_commentary_disclaimer.shtml . 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: http://www.cboe.com/LearnCenter/pdf/characteristicsandrisks.pdf

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 http://www.csfb.com/researchandanalytics.

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.


http://www.csfb.com/legal_terms/market_commentary_disclaimer.shtml




http://www.cboe.com/LearnCenter/pdf/characteristicsandrisks.pdf

not with a bang, but a whimper - credit suisse

Documents