determinants of oil price as on 6-2-2016.doc
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Determinants of Oil Price: A Markov Regime Switching Approach
M.Thenmozhi*and N. Srinivasan**
Abstract
This study examines the impact of fundamental, financial and speculative factors on crude oil prices
and analyzes the behavior of various determinants with respect to volatile regimes. rior research has
focused on the impact of demand, supply and other macroeconomic factors. !hile financialization
and speculative activity in oil derivative segment has created the need to examine the impact of "#$
month basis and non$commercial net long positions %futures and options& on crude oil prices. This
study differs from previous literature by examining the impact of speculative factors on oil price at
low and high volatile regimes using Mar'ov regime$switching model. !e contribute by controlling
for emerging mar'et oil consumption and trade$weighted (S dollar %)road& ndex apart from other
demand and supply factors, we also control for stoc' index to examine the effect on oil prices. +urempirical findings indicate that speculation affects the oil price positively in low$volatile state and has
inverse effect in high$volatile state. t low$volatile regimes, fundamental, financial and speculative
factors have significant impact on the oil price, whereas at high volatile regimes, only the factors
pertaining to supply, S- // and trade$weighted (S dollar %)road& ndex have a significant effect
on the oil price. )roadly, the results imply that the effect of speculation on the oil price can only be
seen in low$volatile regimes, whereas, in high$volatile regimes, supply and financial factors play a
significant role in explaining the oil price. +ur results suggest that regulators and policyma'ers
should consider supply dynamics while trac'ing or predicting the movements of the oil price,
particularly, during high$volatile periods.
Keywords0 1rude oil, Speculation, Mar'ov 2egime Switching Model
*rofessor, 3epartment of Management Studies, ndian nstitute of Technology Madras, 1hennai 4 5///65, ndia,
mtm7iitm.ac.in
**2esearch scholar, 3epartment of Management Studies, ndian nstitute of Technology Madras, 1hennai 4 5///65,
ndia, sin.iitm7gmail.com
1. Intro!ction
#This index consists of the seven %euro, 1anadian dollar, 8apanese yen, )ritish pound, Swiss franc, ustralian dollar andSwedish 'rona&
mailto:sin.iitm@gmail.commailto:sin.iitm@gmail.com -
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1rude oil price plays a significant role in the world economy and has always been in the forefront of
discussions, regardless of the macroeconomic situation that prevails in both developed and
developing economies. +il is one of the highly traded commodities in the world with high
participation from financial institutions in the derivative segment and they play an active role in
establishing the price of the crude oil. The economy becomes more difficult to manage when the oil
prices remain highly volatile, as higher volatility in crude oil prices, have greater ramifications for
different players in the economy and managing current account balance for governments becomes a
challenge.
recise estimation of the factors that affect the crude oil price helps in understanding the dynamics of
crude oil price movements and managing the ris' pertaining to volatile oil prices. The determinants of
the crude oil price in the high$volatile period might be different from low$volatile period, and may
differ during different economic phases. !e differ from prior research, by investigating the effect of
fundamental, financial and speculative factors on the crude oil prices at high and low volatility
regimes.
Most of the previous studies focused on oil supply and demand factors and provide evidence that
fundamental factors are the 'ey drivers of oil prices %1hevillon and 2ifflart, #//9: eltonen et al.,
#/"": ;ilian, #//9&. !ith respect to crude oil supply factors, such as +
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%Naifar and 3ohaiman, #/"6&, but has not been used to estimate the effect of multiple factors on oil
prices at different regimes. @ence, the study uses Mar'ov regime switching model to investigate the
nonlinear relationship between the crude oil and its determinants at different regimes.
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#. Methoolog$
!e examine the stationarity of the variables using ugmented 3ic'ey Fuller, hillip erron and
;SS tests, and test for non$linearity using )3S test. The Mar'ov regime$switching model is
developed using Matlab 2#/"#a.
%DS &est for 'on(linearit$
resence of non$linear dependence in the data is tested using the )3S non$linearity test proposed by
)roc' et al.%"9DJ, "995&.The presence of non$linearity is confirmed if the test statistic is greater than
the critical value of the standard normal distribution at the specified confidence levels. The )3S non$
linearity test based on the correlation integral of the time series is as follows0
"% , & % , &% , & K .
% , &
m
m
m
m
T C T C T W T
T
%"&
where, represents the )3S test statistic, stands for the standard deviation of ,
m is the embedding dimension, and L represents the maximum difference between pairs of
observations considered in calculating the correlation integral. The )3S test statistic is
asymptotically normally distributed with zero mean and unit variance i.e., N %/, "&. The null
hypothesis of the )3S procedure is that the data are independently, identically distributed %i.i.d&. The
null hypothesis of linearity is reAected if the computed test statistic exceeds the critical value at the
convention level. The reAection of the null hypothesis indicates the presence of nonlinear dependence
in the data.
&he Markov(Switching moel
Several studies in the literature have used Mar'ov regime$switching models to investigate non$
linearity and asymmetry %@amilton, "9D9: Hray, "995: ;rolzig, "99D: ;rolzig, #///: rtis et al.,
#//?&. @amilton %"9D9& proposed that 2egime shifts in mean and variance in a time series variable ty
can be modeled using Mar'ov regime$switching autoregressive model %MS$2& of pth order as
follows
%#&
where Oiis the slope coefficient of the autoregressive term %yt P "&. Q and R are the mean and standard
deviation based on the state at time t %st& andytrepresents the !T crude oil price. This MS$2
methodology allows us to model the potential regime shifts in the crude oil price. ;rolzig %"99D&
developed MS$C2, which is a generalization of the MS$2 model %@amilton, "9D9& and used to
find the causal relationship between endogenous variables. Several existing literature used MS$C2
for this purpose %;rolzig, "99J: !arne, #///: sarada'is et al., #//&. n these models, the intercept
#This index consists of the seven %euro, 1anadian dollar, 8apanese yen, )ritish pound, Swiss franc, ustralian dollar andSwedish 'rona&
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term, autoregressive slope coefficient and the error variance are regime dependent. The Mar'ov
regime switching regression is modeled as follows0
%6&
=et us assume that rt as dependent variable and xt as independent variable. ut is the innovationprocess, with variance v%st& based on the state stat time t, follows an irreducible two$state Mar'ov
process defined by the transition probabilities %Pij& between states as follows0
% "& ,ij t t P p s j s i= = = !ith#
"
"ij
j
P=
= for all i,j ", #,
!here,
P""Kp%stK "Us%tP "&K "&
P"#K " PP""Kp%stK "Us%tP "&K #&
P#"K " PP#"K " PP##Kp%stK #Us%tP "&K "&
P##Kp%stK #Us%tP "&K #&.
The Mar'ov regime switching regression model captures potential regime shifts in the data. )ut,
ignoring structural brea's in explaining the data may lead to misleading conclusions. ncorporating
the regime$switching feature of the economic process leads to a better forecasting result %;rolzig,
#///&. +ur model is the generalization of the MS$C2B Mar'ov regime switching regression modelproposed by ;rolzig %"99J&. (sing this model, we explain the dynamics of the !T crude oil spot
price using potential determinants from fundamental and speculation factors.
%?&
where kj is the slope coefficient of the independent variables, which is state$dependent %st&: kj is
the slope coefficient of the dummy variables: utis the innovation process with variance v%st& based on
the state %st&. The slope coefficient of the independent variables and the variance of the error term is
state dependent %st&. @owever, the intercept and dummy variables are not state dependent.
!e model Mar'ov 2egime Switching 2egression %Model 6& as follows0
The fundamental, financial, and speculative factors of crude oil are analyzed to understand the
relative importance of these factors. n these models, the intercept term, independent variableGsV slope
coefficient and the error variance are regime dependent. The Mar'ov regime switching regression is
modeled as follows0
#This index consists of the seven %euro, 1anadian dollar, 8apanese yen, )ritish pound, Swiss franc, ustralian dollar andSwedish 'rona&
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!here is two state mar'ov process, !T crude oil price is used as dependent variable. Net long
pos represents non$commercial traderGs net long position, S- represents the S- // index, 3ollar
index represents the trade$weighted (S dollar index %)road&, basis represents the "#$month basis
between !T crude oil Futures and Spot, lagged !T represents the lagged values of the crude oil
price, +
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+
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t is observed from Figure .# that the transition between the states have occurred only once, i.e., in
the middle of #//J and returned to its initial state by #//D. The results indicate that speculation is not
the only factor that contributes to the changes in the !T oil price.
/ig +.": 4onitional Means olatilities Smoothe &ransition Probalities for Moel 1
0 50 100 150 200 250-0.4
-0.2
0
0.2
0.4
Explained Variable #1
0 50 100 150 200 2500.0725
0.073
0.0735
0.074
0.0745
Conditional Std of Equation #1
0 50 100 150 200 2500
0.5
1
1.5
TimeSm
oothed
States
Prob
abilities
State 1
State 2
b.8 *ffect of spec!lation on the oil price controlling for financial factors
The impact of speculative factor on !T oil prices controlling for financial factors Model # of Table
.6 indicate that in both low$volatile regime and high$volatile regime the impact of non$commercial
traderGs net longpositionon the !T oil price is significant at "X. t implies that interaction between
the financial factors and the speculative factor explains the !T oil price formation.
The impact of dollar index on the !T oil price in high$volatile regime is insignificant, whereas in
low$volatile regime it is significant at "X. This indicates that dollar index plays a significant role in
the times of normal mar'et phases. @owever, during bullish and bearish mar'et periods dollar index
fails to explain the change in the oil price. The negative sign in the low$volatile regime indicates that
the (S dollar appreciation have negative effect %P& on oil price, whereas depreciation of the (S dollar
have positive effect %Y& on the oil price.
)asis has insignificant impact on the !T oil price in both high$volatile regime and low$volatile
regime. This indicates that basis have no significant role in the determination of oil price during all
mar'et phases %Normal, )earish, and )ullish&.
The impact of S- // on !T oil price is insignificant in low$volatile regime, whereas in high$
volatile regime it is significant at "X. This indicates that stoc' mar'et index explains the crude oil
price only in times of normal mar'et phases. @owever, during bullish and bearish mar'et periods,
#This index consists of the seven %euro, 1anadian dollar, 8apanese yen, )ritish pound, Swiss franc, ustralian dollar andSwedish 'rona&
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stoc' mar'et index fails to explain the dynamics in the oil price. t is expected to have an inverse
relationship with the oil price, but a positive relationship is observed between the stoc' mar'et index
and oil price. 2ise in the price of oil might be due to the increased consumption of the crude oil
during economic expansion.
The duration of the regime " is ".#D and regime # is ./#. This shows that volatility of the crude oil
conditioned on combined speculative and financial factor is high, that is, the oil price is more volatile.
The level of speculation is significant irrespective of the regime when controlled for financial factors.
The difference in the model variance between the two states indicates that the variation in crude oil
price is explained more by speculative and financial factors in high$volatile states than in the low$
volatile state.
/ig +.#: 4onitional Means olatilities Smoothe &ransition Probalities for Moel "
0 50 100 150 200 250-0.4
-0.2
0
0.2
0.4
Explained Variable #1
0 50 100 150 200 2500.04
0.05
0.06
0.07
0.08
Conditional Std of Equation #1
0 50 100 150 200 2500
0.5
1
TimeS
m
oo
thedS
tatesP
robabilities
State 1
State 2
Figure .6 portrays that there is a freWuent switchover between the two states. The results indicate that
speculation combined with financial factors explains the changes in the !T oil price.
c.8 Relative importance of eterminants of the oil price
The impact of speculative factors on the !T oil price controlling for both fundamental and financial
factors analyzed using Mar'ov 2egime$Switching Model %Model 6 of Table .6& shows that the
impact of non$commercial traderGs net long position on the !T oil price is insignificant in low$volatile regime, whereas it is significant at "X in high$volatile regime. t implies that speculative
factor explains the movements in !T oil price only in high$volatile regime when controlled for both
financial and fundamental factors.
The dollar index is significant at X in low$volatile regime, whereas in high$volatile regime it is
significant at "X. This indicates that the dollar index has significant impact on the !T oil price
#This index consists of the seven %euro, 1anadian dollar, 8apanese yen, )ritish pound, Swiss franc, ustralian dollar andSwedish 'rona&
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regardless of state. This implies that dollar index plays a significant role in all mar'et phases. n low$
volatile regime, it has significant negative impact, whereas in high$volatile regime it has significant
positive impact.
)asis has insignificant impact on the !T oil price in low$volatile regime, whereas it is significant at
"X in high$volatile regime. This indicates that basis have significant role in determining the oil price
in bearish and bullish mar'et phases and its effect is insignificant during normal mar'et phase.
S- // has significant impact on the !T oil price irrespective of its state and is significant at "X
in both regimes. This indicates that stoc' mar'et index explains changes in crude oil price in all
mar'et phases. significant positive relationship is observed in low$volatile period, whereas a
significant negative relationship observed in high$volatile regime.
The empirical results indicate that the =agged !T oil price plays a vital role in estimating the price
of crude oil. The lagged !T oil price is significant at "X in both regimes. There is a significant
positive relation between the lagged oil price and oil price in low$volatile regime whereas in high$
volatile regime it is negative relation.
The +
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The duration of the state " is "5.5D and state # is ".5". This indicates that the volatility of the crude oil
explained by combination speculative, fundamental, and financial factors. The level of speculation is
significant in high$volatile regime indicating that speculative factor has significance in determining
the oil price only in high$volatile phase when combined with other factors. The difference in the
model variance between the two states indicate that the variation in crude oil price is better explained
by speculative, fundamental, and financial factors in low$volatile state compared to the high$volatile
state.
From Model 6 of Table .6, The predominant factors influencing oil price are +
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speculative variable when controlled for fundamental and financial factors have a significant role in
explaining the !T oil price in high volatility state. t high$volatility regimes, we observe that
factors pertaining to speculation combined with financial and fundamental factors have a significant
effect on the oil price, while at low$volatility regimes, it is the fundamental and financial variables
that have a significant role in !T crude oil price discovery.
+
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Fattouh, )., ;ilian, =., - Mahadeva, =. %#/"#&. Te +ole of /pe!ulation in $il Markets0 Wat1ave We 2earned /o ar34 rs(. vom $xford Institute for %ner(y /tudies. !or'ing aper ?. m". ugust im nternet unter0 http0BBwww. oxfordenergy.orgBwpcmsBwpcontentBuploadsB#/"#B/6B!M$?. pdf.
Fallahi, F. %#/""&. 1ausal relationship between energy consumption %
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2eboredo, 8. 1. %#/"/&. Nonlinear effects of oil shoc's on stoc' returns0 a Mar'ov$switching
approach.;pplied %!onomi!s. http0BBdoi.orgB"/."/D/B///65D?/D/#6"?5/5.
Sornette, 3., !oodard, 2., - ]hou, !. E. %#//9&. The #//54#//D oil bubble0
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-3
-2
-1
0
1
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3
4
5
-3
-2
-1
0
1
2
3
4
5
96 97 98 99 00 01 02 03 04 05 06 07 08 09 10 11 12 13 14
WTI CRUDE OILSPOTPRICE
NON COMMERCIAL NET LONG POSITION
-2
-1
0
1
2
3
-2
-1
0
1
2
3
96 97 98 99 00 01 02 03 04 05 06 07 08 09 10 11 12 13 14
WTI CRUDE OILSP OTPRICE
TRADE WEIGHTED DOLLAR INDEX
-3
-2
-1
0
1
2
3
-2
-1
0
1
2
3
4
96 97 98 99 00 01 02 03 04 05 06 07 08 09 10 11 12 13 14
WTI CRUDE OILSPOT PRICE
S & P 500
-5
-4
-3
-2
-1
0
1
2
3
-3
-2
-1
0
1
2
3
4
5
96 97 98 99 00 01 02 03 04 05 06 07 08 09 10 11 12 13 14
WTI ASIS
-4
-3
-2
-1
0
1
2
3
4
-3
-2
-1
0
1
2
3
4
5
96 97 98 99 00 01 02 03 04 05 06 07 08 09 10 11 12 13 14
WTI CRUDE OILSPOT PRICEOECD IMPORTS
0
20
40
60
80
100
120
140
96 97 98 99 00 01 02 03 04 05 06 07 08 09 10 11 12 13 14
WTI CRUDE OIL SPOT PRICE
-4
-3
-2
-1
0
1
2
3
4
-3
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-1
0
1
2
3
4
5
96 97 98 99 00 01 02 03 04 05 06 07 08 09 10 11 12 13 14
WTI CRUDE OILSPOT PRICE
OECD CONSUMPTION
-4
-3
-2
-1
0
1
2
3
-3
-2
-1
0
1
2
3
4
96 97 98 99 00 01 02 03 04 05 06 07 08 09 10 11 12 13 14
WTI CRUDE OILSPOTP RICES
OECD IN!ENTOR"
-2#0
-1#5
-1#0
-0#5
0#0
0#5
1#0
1#5
2#0
-3
-2
-1
0
1
2
3
4
5
96 97 98 99 00 01 02 03 04 05 06 07 08 09 10 11 12 13 14
WTI CRUDE OILSPOT PRICE
OPEC PRODUCTION
-4
-3
-2
-1
0
1
2
3
-3
-2
-1
0
1
2
3
4
96 97 98 99 00 01 02 03 04 05 06 07 08 09 10 11 12 13 14
WTI CRUDE OILSPOT PRICE
TOTALOIL RIGCOUNT
-1#2
-0#8
-0#4
0#0
0#4
0#8
1#2
1#6
2#0
2#4
2#8
-4
-3
-2
-1
0
1
2
3
4
5
6
96 97 98 99 00 01 02 03 04 05 06 07 08 09 10 11 12 13 14
WTI CRUDE OILSPOTPRICEINDUSTRIALPRODUCTION IN INDIA
-1#5
-1#0
-0#5
0#0
0#5
1#0
1#5
2#0
-3
-2
-1
0
1
2
3
4
96 97 98 99 00 01 02 03 04 05 06 07 08 09 10 11 12 13 14
WTI CRUDE OILSPOTPR ICE
INDUSTRIALPRODUCTION IN CHINA
#This index consists of the seven %euro, 1anadian dollar, 8apanese yen, )ritish pound, Swiss franc, ustralian dollar andSwedish 'rona&
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