not with a bang, but a whimper - credit suisse
TRANSCRIPT
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
January 2018 For Institutional Clients Only
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
January 2018 For Institutional Clients Only
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
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
Source: Milliman
January 2018 For Institutional Clients Only
Source: Credit Suisse Equity Derivatives
Long Convexity/Low Carry Tail Strategies Gain in Popularity
Public Pensions’ Asset Allocation Steady Over Last 5 Years
10
Derivatives Usage Trends
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
January 2018 For Institutional Clients Only
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
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.
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
January 2018 For Institutional Clients Only
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
January 2018 For Institutional Clients Only
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
January 2018 For Institutional Clients Only
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
January 2018 For Institutional Clients Only
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
)
Monthly Change in Yields (Net %)
Chg in 10Y Yield vs. Chg in VIX (3M)
R2 = 0.01
-30
-20
-10
0
10
20
30
40
-1 -0.5 0 0.5 1C
han
ge in
VIX
(P
ts)
Monthly Change in Yields (Net %)
Chg in 10Y Yield vs. Chg in VIX (6M)
R2 = 0
Source: CS Equity Derivatives Strategy
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
January 2018 For Institutional Clients Only
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
Source: CS Equity Derivatives Strategy Source: CS Equity Derivatives Strategy
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)
January 2018 For Institutional Clients Only
-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
Source: CS Equity Derivatives Strategy
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
January 2018 For Institutional Clients Only
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)
Source: CS Equity Derivatives Strategy
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)
January 2018 For Institutional Clients Only
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
January 2018 For Institutional Clients Only
60
70
80
90
100
110
120
130
140
6
8
10
12
14
16
18
20
22
24
Jan-17 Mar-17 May-17 Jul-17 Sep-17 Nov-17 Jan-18
VIX Index (LHS)
VVIX Index (RHS)
0
2
4
6
8
10
12
Jan-07 Jan-09 Jan-11 Jan-13 Jan-15 Jan-17
Ra
tio
VVIX/VIX Ratio
Source: CS Equity Derivatives Strategy Source: CS Equity Derivatives Strategy
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)
Source: CS Equity Derivatives Strategy
January 2018 For Institutional Clients Only
VIX Scenarios
Is Low Vol a Bubble?
21 January 2018 For Institutional Clients Only
22
Is Low Vol a Bubble?
Source: CS Equity Derivatives Strategy
January 2018 For Institutional Clients Only
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 Derivatives Strategy
January 2018 For Institutional Clients Only
Source: CS Equity Research
Source: CS Equity Research
24
Volatility Was Low in 2017…
Source: CS Equity Derivatives Strategy
January 2018 For Institutional Clients Only
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)
Source: CS Equity Derivatives Strategy
Median VIX vs. Min/Max Range
25
…But NOT Cheap
Source: CS Equity Derivatives Strategy
January 2018 For Institutional Clients Only
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
Source: CS Equity Derivatives Strategy
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?
Source: CS Equity Derivatives Strategy
January 2018 For Institutional Clients Only
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
January 2018 For Institutional Clients Only
Source: CS Equity Research
Source: CS Equity Research
-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
January 2018 For Institutional Clients Only
Source: CS Equity Derivatives Strategy
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
29 January 2018 For Institutional Clients Only
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
January 2018 For Institutional Clients Only
-2.8
-2.7
-2.6
-2.5
-2.4
-2.3
-2.2
-2.1
-2
-1.9
Jan-17 Mar-17 May-17 Jul-17 Sep-17 Nov-17 Jan-18
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.
January 2018 For Institutional Clients Only
S&P 1Y Call Skew Trade Payoff Diagram
Source: CS Equity Derivatives Strategy
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.
January 2018 For Institutional Clients Only
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
Source: CS Equity Derivatives Strategy
Structure Expiry StrikeTarget
Volatility
Indicative
Offer
SPX Timer Call 21-Dec-18 100% 6.50% 3.18%
SPX Timer Call 21-Dec-18 100% 7.50% 3.60%
SPX Timer Call 21-Dec-18 100% 8.50% 3.95%
SPX Timer Call 21-Dec-18 100% 9.50% 4.27%
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.
January 2018 For Institutional Clients Only
Source: CS Equity Derivatives Strategy
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
January 2018 For Institutional Clients Only
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.
January 2018 For Institutional Clients Only
EEM vs. SPX Performance Since Jan 2008
Source: CS Equity Derivatives Strategy
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.
Source: CS Equity Derivatives Strategy
January 2018 For Institutional Clients Only
-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)
Source: CS Equity Derivatives Strategy
37
Top Sector Picks for 2018
CS US Equity Strategy team has the following GIC sector recommendations:
Breaking it down further:
January 2018 For Institutional Clients Only
Source: CS Equity Research
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
January 2018 For Institutional Clients Only
0.86
0.88
0.9
0.92
0.94
0.96
0.98
Jan-17 Mar-17 May-17 Jul-17 Sep-17 Nov-17 Jan-18
Skew
(R
atio
)
KRE 6M Call Skew (10D/40D)
KRE Upside Skew in the 82nd %tile High
Trade Payoff Diagram
Source: CS Equity Derivatives Strategy
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.
January 2018 For Institutional Clients Only
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
January 2018 For Institutional Clients Only
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
Source: CS Equity Derivatives Strategy
Source: CS Equity Derivatives Strategy
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.
January 2018 For Institutional Clients Only
Source: CS Equity Derivatives Strategy
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.
January 2018 For Institutional Clients Only
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
Source: CS Equity Derivatives Strategy
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.
January 2018 For Institutional Clients Only
Correlation Btw Global Equity Markets ~10Y Low
Put Premium Cost Comparisons (Dec’18 90%
Individual vs. Basket Puts)
Source: CS Equity Derivatives Strategy
Source: CS Equity Derivatives Strategy
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
Jan-08 Jan-10 Jan-12 Jan-14 Jan-16 Jan-18
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)
January 2018 For Institutional Clients Only
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.
January 2018 For Institutional Clients Only
Source: Credit Suisse Equity Derivatives
CS Equity Derivatives Monthly Macro Call
46 January 2018 For Institutional Clients Only
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.
47 January 2018 For Institutional Clients Only