determinants of oil price as on 6-2-2016.doc

7/26/2019 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:[email protected]:[email protected]


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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



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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



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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,



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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



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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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4

5

-3

-2

-1

0

1

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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

-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


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


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


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


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