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Shale Revolution and Shifting Crude Dynamics Liuren Wu Joint work with Malick Sy Baruch College July 8, 2018 Liuren Wu (Baruch) Shifting Crude Dynamics 7/8/2018 1 / 20
Shale Revolution and Shifting Crude Dynamics
Liuren WuJoint work with Malick Sy
Baruch College
July 8, 2018
Liuren Wu (Baruch) Shifting Crude Dynamics 7/8/2018 1 / 20
Estimating and managing the risk of oil price shocks
Crude price fluctuation sends shocking waves to all segments of the economy.
A large body of literature is devoted to estimate and manage the associatedrisks induced by the oil price fluctuation.
1 Risk assessment: Brown &Yucel (2002), Jones, Leiby, &Paik (2004),Huntington (2005), ...
Quantify the (negative) impacts of oil price hike on the aggregateeconomy.
2 Risk management: Carter,Rogers, & Simkins (2006), Morrell & Swan(2006), ...
Hedging crude fluctuation for airline industry: why/whether hedgingfuel cost can enhance firm performance
Evidence is positive on average, but recent hedges led to large losses...
Crude price fluctuation can come from both supply and demand shocks.
The two types of shocks generate different risk profiles and ask fordifferent risk management actions.
Kilian (2009): structural VAR to capture two-way interaction
Liuren Wu (Baruch) Shifting Crude Dynamics 7/8/2018 2 / 20
Capturing time-varying contribution fromdemand v. supply shocks
The relative contribution of supply and demand shocks can vary stronglyover time.
Major events and structural changes can induce large variations in theintensities of the two types of shocks and fundamental shifts in theirrelative contribution.
It is important to timely and accurately predict the time variation in therelative contribution for accurate risk assessment and risk management.
Airline fuel cost hedging depends crucially on the relative compositionof the supply/demand shocks
The intuition is to hedge supply shocks, but not demand shocks.
We propose a new methodology to estimate the time variation of therelative contribution using options on the stock index and crude oil futures,without pre-specifying the dynamics for the variation.
Liuren Wu (Baruch) Shifting Crude Dynamics 7/8/2018 3 / 20
Project oil price movement to the stock market variation
Take the S&P 500 index (SPX) as a proxy for demand variation
dDt/Dt =
√vdt dW
dt
We focus on aggregate economic demand rather than oil demand.
Choosing a financial security index with actively traded options helpsthe identification
Project crude futures price movements to the stock index,
dOt/Ot = ηdt
√vdt dW
dt − ηst
√v st dW
st
Think CAPM, with time-varying beta (ηdt ).Treat the projection residual as demand-independent supply shocks.
The focus is on the variance, not the drift ...
Direction prediction is too hard.
Risk prediction is a bit easier, and it can also be very useful.
Liuren Wu (Baruch) Shifting Crude Dynamics 7/8/2018 4 / 20
Identification without specification
We allow the variance rates (vdt , v
st ) and loadings (ηdt , η
st ) to vary randomly,
but without specifying how.
Had we specified the full dynamics, we could have derived the option pricingimplications and estimate the dynamics with option prices.
We choose not to do this
Standard stochastic variance specification often takes the form of atime-homogeneous mean-reverting process, not particularly helpful foridentifying structural shifts.
Accurately estimating regime switching dynamics often asks forrepeated historical occurrence of the regimes, not particularly helpfulfor short samples, or new regimes.
We consider a new modeling approach that allows us to extract the currentstate of things (such as the variance rates vd
t , vst ) without the need to know
how they move in the future.
Liuren Wu (Baruch) Shifting Crude Dynamics 7/8/2018 5 / 20
Identify demand intensity from SPX options
dDt/Dt =√
vdt dW
dt
Instead of specifying the full dynamics vdt , we specify the local variation of
the SPX option implied volatility for each contract (K ,T ),
dI dt (K ,T )/I dt (K ,T ) =
√ωdt dZ
dt , Et [dZ
dt dW
dt ] = ρtdt,
ρt < 0 captures the volatility feedback effect on the stock market portfolio:market risk ⇑ → discount rate ⇑→ valuation ⇓Perform instantaneous P&L attribution and take risk-neutral expectation
0 = EQt
[dB
dt
]= Bt +
1
2BDDD
2t v
dt +
1
2BII (ω
dt )(I dt )2 + BDIDt Itγ
dt , (1)
wth γdt =√vdt ω
dt ρ
dt being the return-implied volatility covariance.
(1) can be regarded as a moment-condition based pricing equation:The current option price on this contract must satisfy the constraintimposed by (1) in terms of the index’s current variance vd
t , the optionimplied volatility’s variance ωt , and their covariance γt .
Nothing is said about how these variance/covariance vary over time.
Liuren Wu (Baruch) Shifting Crude Dynamics 7/8/2018 6 / 20
From implied volatility smiles to variance/covariance
Plug in the greeks, assume parallel proportional shifts on the smile (aroundthe money), we can approximate the smile with a quadratic equation:
I 2t (k) ≈ Adt + 2γdt k + ωd
t k2
The at-the-money variance Adt ≈ vd
t approximates the variance rate.The smile slope approximates the covariance,
Sdt ≡
∂I 2t∂k
∣∣∣∣k=0
= 2γdt ≈1
2ζdt
with ζdt being the return-variance covariance
ζdt ≡ E[dvd
t
vdt
,dDt
Dt
]≈ 2Sd
t
We can infer the variance vdt and covariance ζdt from the SPX option
implied variance Adt and skew Sd
t .
Liuren Wu (Baruch) Shifting Crude Dynamics 7/8/2018 7 / 20
Project crude on SPX
dOt/Ot = ηdt
√vdt dW
dt − ηst
√v st dW
st
We can think of the above decomposition as a projection of crude futuresreturn onto the market portfolio (SPX) and treat dW s
t as the residual.
By projection, Et [dWst dW
dt ] = 0.
By classic asset pricing theory, there is no feedback effect on idiosyncraticrisk, Et [dW
st dv
st ] = 0.
From the at-the-money variance and skew on crude futures options, we have
Aot = (ηdt )2vd
t + (ηst )2v st = (ηdt )2Ad
t + (ηst )2v st .
Sot = 1
2E[dvo
t
vot, dOt
Ot
]=
(ηdt )3vd
t
vot
12E[dvd
t
vdt, dDt
Dt
]=
(ηdt )3Ad
t
Aot
Sdt .
Combining the two smiles gives us the demand loading (ηdt ) and the relativevariance contribution of the demand shocks (RC d
t ):
ηdt =
(Sot A
ot
Sdt A
dt
)1/3
, RC dt =
(ηdt )2Adt
Aot
.
Liuren Wu (Baruch) Shifting Crude Dynamics 7/8/2018 8 / 20
Constructing floating implied variance and skew series
SPX options are listed at CBOE. Crude (WTI) futures options at CME.
Options contracts are with fixed strikes and expiry dates.
We choose three-month as the pivot point and construct the at-the-moneyimplied variance (At) and implied variance skew (St) from the optionobservations.
Convert option prices into BMS implied volatilities.
At each observed maturity, perform local quadratic regression togenerate implied volatility estimates at floating moneyness levels k
Linear interpolation on total variance to obtain estimates at 3-monthmaturity.
Shorter maturity is noisier. Longer maturity is sparse. A quarter horizon isabout right for airline hedging.
Liuren Wu (Baruch) Shifting Crude Dynamics 7/8/2018 9 / 20
Time-variation of the ATM implied volatilities
04 05 06 07 08 09 10 11 12 13 14 15 16 170
10
20
30
40
50
60
70
80
90A
TM
impl
ied
vola
tility
, %WTI
SPX
The two series show more independent variations during the first half of thesample, but more comovements during the second half.
Cross-correlation between daily log changes: 26% before 2010, 41% after.
Liuren Wu (Baruch) Shifting Crude Dynamics 7/8/2018 10 / 20
Time-variation of the implied volatility skew
04 05 06 07 08 09 10 11 12 13 14 15 16 17-0.7
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0
0.1
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0.3Im
plie
d va
rianc
e sk
ewWTI
SPX
SPX skew is always negative: Volatility feedback effect (among others)
WTI skew is virtually zero in the first half, but becomes highly negative inthe second half.
Liuren Wu (Baruch) Shifting Crude Dynamics 7/8/2018 11 / 20
Shifting demand shock contribution to crude movements
04 05 06 07 08 09 10 11 12 13 14 15 16 170
10
20
30
40
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60
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80
90
100V
aria
nce
co
ntr
ibu
tion
fro
m d
em
an
d s
ho
cks,
%
Demand shock contributes little to crude movements before 2009, but over50% since then.
What’s driving the shift and what’s the implication?
Liuren Wu (Baruch) Shifting Crude Dynamics 7/8/2018 12 / 20
Historical variation of crude futures prices
04 05 06 07 08 09 10 11 12 13 14 15 16 1720
40
60
80
100
120
140
160O
il prices, $/b
bl
WTI
Brent
Crude price had been on an upward trend since 2004, until the 2008financial crisis.
The crisis represents a huge negative demand shock to the crude price,adding the contribution of demand shocks to the crude price movements.
Liuren Wu (Baruch) Shifting Crude Dynamics 7/8/2018 13 / 20
The US shale revolution
04 05 06 07 08 09 10 11 12 13 14 15 16 1710
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30
40
50
60O
PE
C p
rodu
ctio
n, m
bb/d
1
2
3
4
5
6
US
tigh
t oil,
mbb
/d
OPEC production has been stable over the sample period.
US tight oil production has picked up pace since 2010, from negligible to17% of OPEC production.
Liuren Wu (Baruch) Shifting Crude Dynamics 7/8/2018 14 / 20
Shifting OPEC behavior since the shale revolution
A. 2004-2010 B. 2011-2016
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Co
rr(
Price
t, P
rod
uctio
nt+
L)
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Lag, Months
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0
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rr(
Price
t, P
rod
uctio
nt+
L)
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Lag, Months
OPEC production used to respond strongly to crude (Brent) pricemovements,
but no longer since the shale revolution
Liuren Wu (Baruch) Shifting Crude Dynamics 7/8/2018 15 / 20
Shifting crude dynamics and market sentiments
The financial crisis represents a large negative demand shock that put a dentto the crude price.
The subsequent rise of the shale revolution has fundamentally altered thecrude supply behavior.
The increasing U.S. shale oil production at a competitive cost has undercutthe price-setting power of the OPEC, and lowered the OPEC’s incentive toself-regulate its production.
As a result of the shift in dynamics, investors have also shifted from beingconcerned with crude oil price hikes as a gauge of production cost, toworrying about crude oil price declines as an indication of weakening marketdemand.
Crude futures option implied volatilities turned from showing positiveor no skew to showing negative skew.
Liuren Wu (Baruch) Shifting Crude Dynamics 7/8/2018 16 / 20
Implications for optimal fuel cost hedging
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1O
ptim
al fu
el c
ost h
edgi
ng ra
tio, h
t
Full fuel cost hedging is optimal historically, when oil price fluctuation ismostly supply driven.
Only partial hedge is optimal in the current demand-driven crude market.
Liuren Wu (Baruch) Shifting Crude Dynamics 7/8/2018 17 / 20
Hedging loss at Cathay Pacific.
The loss comes from (i) a drop in travel business and (ii) loses from hedging.
These two rarely come together in supply-driven crude market – that’s thepurpose of hedging.
But they tend to come together in demand-driven crude market conditions –hedging is less desirable.Liuren Wu (Baruch) Shifting Crude Dynamics 7/8/2018 18 / 20
Delta loss to crude hedging
The $4bn loss in the last 8 years is not due to “wrong bet,” but due to“wrong hedge.”
Crude movements during the last 8 years are much more driven by demandthan supply, and asking for less or no fuel cost hedging.Liuren Wu (Baruch) Shifting Crude Dynamics 7/8/2018 19 / 20
Ignore the shifting market condition at your own peril
It is difficult to predict whether the crude price will go up or down.
Delta CEO Bastian: “I don’t get paid to make those kinds of bets.”
Predicting the second moments (variance/covariance) is much easier,especially with options.
We can infer the time-variation in the relative contribution of demand shocksto the crude price movements from stock index and crude futures options,
without making directional bets,
without pretending to know whether there are different regimes andhow they transit from one to another.
The inferred relative contribution can be used to determine the optimal fuelhedging ratio, which can drastically reduce the cost/loss of the foolhardypractice of full fuel hedge.
In a demand-driven market, the full hedge fully exposes the airline todemand shocks.
Liuren Wu (Baruch) Shifting Crude Dynamics 7/8/2018 20 / 20
