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Synopsis of

OIL PRICE DETERMINANTS AND CO-MOVEMENT DYNAMICS

A THESIS

to be submitted by

SRINIVASAN N

for the award of the degree

of

MASTER OF SCIENCE

(By Research)

DEPARTMENT OF MANAGEMENT STUDIES

INDIAN INSTITUTE OF TECHNOLOGY MADRAS, INDIA

FEBRUARY, 2016

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OIL PRICE DETERMINANTS AND CO-MOVEMENT DYNAMICS

1. INTRODUCTION

Crude oil is the key driver of a nations economy and volatility in oil price leads to potentialramifications over a countrys economy and its financial markets. Previous research has

focused more on the impact of demand and supply factors influencing oil price. il !eing one

of the highly traded commodities in the world with high participation from financial

institutions in the derivative segment" speculation in crude oil options and futures can play an

active role in esta!lishing the crude oil price. Precise estimation of the factors that affect the

crude oil price helps in understanding the dynamics of crude oil price movements and helps

in managing the risk pertaining to volatile oil prices. il price series e#hi!it structural !reaks

and non$linearity (Re!oredo" %&'&) and may e#hi!it dynamic !ehavior with respect to the

financial events such as crisis" changes in government policy" changes in the !usiness cycles

and economic downturns. he economy !ecomes more difficult to manage when 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 !alance for governments

!ecomes a challenge. he determinants of crude oil price in high$volatile period might !e

different from low$volatile period" and may differ during different economic phases. ence"

an attempt is made in this study to e#amine the effect of fundamental" financial and

speculative factors on crude oil prices during high and low volatile regimes.

*luctuations in crude oil price impacts macroeconomic factors such as growth rate" interest

rate" inflation and e#change rate. Crude oil is actively included in the portfolio of varioushedge funds and varia!ility in oil price has significant linkage with various macroeconomic

indicators of a country. il price has influence on a countrys economic growth and thus on

inflation and interest rate. il prices affect the stock prices either directly !y influencing

future cash flows of a company or indirectly !y affecting the interest rate that is used to

discount the future cash flows of a company. Change in stock prices and e#change rates also

impacts oil prices. But" the nature and e#tent of relationship !etween oil price and

macroeconomic indicators may vary from time to time and understanding the pattern of

relationship across time and fre+uency hori,on !ecomes essential for traders and investors.

ence" we attempt to e#amine the co$movement !etween (i) oil price and stock inde# and (ii)

oil price and e#change rate to capture the pattern of relationship across different time hori,on.

2. LITERATURE REVIEW AND MOTIVATION OF THE STUDY

2.1 Fac!"# $%&'()%c$%* C"(+) O$'

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-ost of the previous studies focused on oil supply and demand factors and provide evidence

that fundamental factors are the key drivers of oil prices (Chevillon and Rifflart" %&&/

Peltonen et al." %&''). 0ith respect to crude oil" supply factors such as P1C production

(Chevillon and Rifflart" %&&) and 1C2 inventory are found to have inverse relationship

with oil prices. 3n the demand side" most of the studies have used only 1C2 consumption

and 1C2 net imports for determining the residual demand shock and these shocks are foundto have positive impact on oil prices (4ilian and 5ee" %&'6). Since past studies considered

only shocks and studied their effect on oil price" the main effect of P1C production" 1C2

inventory" 1C2 consumption and 1C2 net imports individually has !een ignored.

-oreover" previous studies paid little attention to the demand from emerging markets. ence"

there is a need to empirically e#amine the effect of individual supply related varia!les such as

1C2 inventory and P1C production and demand related varia!les such as 1C2

consumption and 1C2 net imports. But" considering 1C2 consumption alone is not

appropriate" since it e#cludes ma7or oil consuming countries like China and 3ndia. ence" use

of pro#y varia!les to account for the increasing consumption from emerging economies suchas China and 3ndia is pertinent to capture the glo!al consumption effectively.

Contemporary research in the field of oil price dynamics indicates that financial factors also

affect oil price apart from fundamental factors. -any studies have shown significant impact

of e#change rate on crude oil prices (Basher et al.,%&'%/ Beckmann and C,uda7" %&'8)" !ut

most of them have used 911R (Breitenfellner et al." %&&)" R11R (riavwote and 1riemo"

%&'%/ Breitenfellner et al." %&&) and :S dollar e#change rate" which is !ased on the

transaction !etween :S and its trading partners. 1#amining the impact of effective e#change

rate of dollar inde# has limitations in accounting for the glo!al trading of oil in dollars.

owever" using a comprehensive measure such as 2ollar inde# (!road) would capture thecomplete dynamics of oil trading. ence" it is pertinent to e#amine the impact of dollar inde#

(!road) on oil price than looking at the impact of effective e#change rate on oil prices.

Prior research have also found significant impact of stock inde# on crude oil prices (Basher

et al.,%&'%/ Cifarelli and Paladino" %&'&/ Breitenfellner et al.,%&&). 0ith the advancement

of financiali,ation" forward and futures market impact oil prices. 3f the e#pected future oil

spot price is greater than the futures price" there will !e a premium to e#tract oil from well.

But" the impact of spread !etween the current spot price and a year ahead futures price of oil

has not !een considered !y prior studies. Considering '%$month !asis which measures the

premium of holding; storing a crude oil rather than a derivative product may provide moreinsight on crude oil price discovery.

Sornette et al." (%&&) postulated that the oil price shocks during crisis are due to speculative

factors and speculative trading can influence the oil prices without any change in

fundamental factors (amilton" %&&

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il price series e#hi!it structural !reaks and non$linearity (Re!oredo" %&'&) and may e#hi!it

dynamic !ehavior with respect to the financial events such as crisis" changes in government

policy" changes in !usiness cycles and economic downturns. =s the !ehavior of the oil price

determinants change over time" understating the oil price and its determinants !ehavior with

respective regimes !ecomes crucial. :sing ordinary regression model fails to identify the

dynamic linkage !etween oil prices and its determinants across regimes. -ost of the e#istingliteratures e#amine the relationship using traditional linear time series models such as >=R;

>1C-" co$integration and structural >=R. owever" oil price is found to have structural

!reaks and may not !e linear and most of the studies e#amine casual; long term relationship

of crude oil with only one or few varia!les. 5inear models could suffer from possi!le

misspecification or omitted varia!le !ias and the relationship !etween oil price and

determinants may vary over time. 3ncorporating or using the model" which accounts for

structural !reak and capturing the effect at different periods would help in accurate estimation

of oil price. >ery few studies have used nonlinear models such as CCC $ ?=RC$- and

Bayesian -odel averaging (Breitenfellner et al., %&&). owever" these models cannotestimate the relationship with respect to different market phases and fail to address structural

!reaks in the data. -arkov Regime$switching model provides a fle#i!le framework to model

structural !reaks" dynamic shifts and dynamic relationships. -arkov$regime switching

methodology is largely used for finding non$linear causality (*allahi" %&'') and volatility

(9aifar and 2ohaiman" %&'8)" !ut has not !een used to estimate the effect of multiple factors

on oil prices at different regimes. ence" there is a need to investigate the nonlinear

relationship and comovement !etween crude oil and its determinants at different volatile

regimes using -arkov switching model which will account for structural !reaks" nonlinearity

and various regimes.

2.2 C!-!))% !& !$' "$c) /$ ac"!)c!%!$c &ac!"#

Previous studies that e#amined the relationship !etween the crude oil and e#change

rates;stock indices indicated inconsistency in results. 5ong$run e+uili!rium e#ists !etween

the crude oil price and e#change rate (riavwote and 1riemo" %&'%). Some argued that

increase in oil prices is associated with the appreciating e#change rate (Basher et al.,%&'%/

Beckmann and C,uda7" %&'8). But other studies argued that increase in oil prices is

associated with the depreciating e#change rate (0ang and 0u" %&'%). 0hile !i$directional

causality e#ists !etween oil price and e#change rates after crisis (2ing and >o" %&'%)" at large

time hori,ons (Benhmad" %&'%) and at higher time scales (iwari et al." %&'8)" 3wayemi and*owowe (%&'') there is no impact of oil price on e#change rates.

*ew studies (Cong et al.,%&&

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dependence !etween commodity and stock market is time varying and symmetrical (2elatte

and 5ope," %&'8).

raders and institutional investors have varied investment hori,ons and different risk profiles

and co$movement !etween oil prices and macroeconomic indicators !ecomes important to

assess the risk profile of countries and the market movements. 0hile traders would preferanalysis !ased on nominal prices" most of the studies have focused on real prices.

Previous literature e#amines the co$movement using traditional time series models such as

5S" >=R; >1C-" co$integration and de$trended correlation analysis" which look into the

time scale of the varia!les. owever" co$movement !etween varia!les may vary across time

and the effect could change at different time hori,ons. >ery few studies have used wavelet

analysis to capture the co$movement dynamics across time and fre+uency scales (iwari et

al." %&'8/ 5oh" %&'8). -oreover" e#isting studies have e#amined the relationship !etween oil

prices and e#change rates; stock indices for one country; few countries" which are mostly

developed markets. >ery few studies have focussed on the relationship !etween the oil pricesand emerging stock markets (Basher and Sadorsky" %&&A/ ammoudeh and 5i" %&&).

Besides" prior studies have not focused on oil importing countries and also analy,ed from

traders perspective considering nominal prices. ence" there is a need to focus on traders and

institutional investors perspective and e#amine the co$movement !etween !enchmark oil

price with (i) nominal e#change rates and (ii) stock indices of ma7or oil$importing countries

using wavelet coherence approach.

. OBECTIVES

he purpose of this study is to e#amine the factors that determine the crude oil price and the

comovement dynamics with macroeconomic factors. 3t is important to understand the factors

affecting crude oil price with respect to the changes in the economic cycles and volatile

regimes. 3t is also pertinent to understand the impact of crude oil price on various

macroeconomic varia!les" particularly for each oil$importing country. ence" the specific

o!7ectives of the study are

i. to e#amine the impact of fundamental" financial" and speculative factors on 03

crude oil prices at high and low volatile regimes.

ii. to e#amine the co$movement !etween oil price and e#change rate across differenttime and fre+uency hori,ons for oil importing countries.

iii. to e#amine the co$movement !etween oil price and Stock 3ndices across different time

and fre+uency hori,ons for oil importing countries.

3. DATA AND METHODOLOGY

3.1 D"$)"# !& c"(+) !$' "$c)4

he study focuses on 03 crude oil traded at 9-1D e#change and the fundamentalvaria!les considered in the study are 5agged 03 oil price" P1C production" 1C2 Stocks"

1C2 consumption" 1C2 9et 3mports" industrial production of China and 3ndustrial

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production of 3ndia. he speculative varia!le used in the study is net long positions of non$

commercial traders. he financial varia!les include '% month !asis" SEP && and trade$

weighted :S dollar 3nde# (Broad). he sample period spans from =pril ' to -ay %&'6

comprising %% o!servations. he monthly data is collected from data!ases such as 1nergy

3nformation =gency" 0orld Bank" St. 5ouis *ederal Reserve (:S=) and the :S Commodity

*utures rading Commission.

0e e#amine the stationarity of the varia!les using =ugmented 2ickey *uller" Phillip Perron

and 4PSS tests" and e#amine the non$linearity using B2S test. 0e use -arkov regime$

switching model to e#amine the impact of (i) Speculation on oil prices/ (ii) Speculation on oil

prices controlling for financial varia!les/ and (iii) Speculation on oil prices controlling for

fundamental and financial varia!les at different regimes. :sing the e+uation given !elow" we

e#plain the dynamics of the 03 crude oil spot price using potential determinants from

fundamental" financial and speculation factors.

(')

where kj is the slope coefficient of the independent varia!les" which is state$dependent (st )/

kj is the slope coefficient of the dummy varia!les/ utis the innovation process with variance

v(st) !ased on the state (st). he slope coefficient of the independent varia!les and the

variance of the error term is state dependent (st). owever" the intercept and dummy varia!les

are not state dependent. he analysis has !een done using -atla!$R%&'6a.

3.2 C!-!))% 5)/))% c"(+) !$' a%+ ac"!-)c!%!$c &ac!"#4

he daily time series data of various !enchmark crude oil prices such as the 03" Brent and

P1C !asket crude oil spot price are used. he P1C !asket crude is used for =sian

countries/ Brent oil price is used for 1urope and 03 oil price is used for the :S. 0e identify

top fifteen oil importing countries !ased on the 13= crude oil import statistics. he data

comprises stock indices of oil$importing countries such as the :S (SPD)" China (SS1&)"

@apan (94)" 3ndia (93*)" South 4orea (4SP3)" ?ermany (2=D)" *rance (C=C)" Spain

(3B1D)" Singapore (*SS3)" 3taly (*S1 -3B)" 9etherlands (=1D)" aiwan (0S1)" urkey

(D:'&&)" 3ndonesia (5F6) and Belgium (B15%&) and the e#change rate of oil$importing

countries such as China (:S2C9)" @apan (:S2@P)" 3ndia (:S239R)" South 4orea(:S24R0)" ?ermany (:S21:R)" *rance (:S21:R)" Spain (:S21:R)" Singapore

(:S2S?2)" 3taly (:S21:R)" 9etherlands (:S21:R)" aiwan (:S202)" urkey

(:S2R)" 3ndonesia (:S232R) and Belgium (:S21:R) are used for the study. 2aily data

for the period starting from Ath @anuary %&&8 to 8&th 2ecem!er %&'6 (8&'% o!servations) has

!een considered" e#cept for the Stock inde# of China (SS1&) which starts from th @anuary

%&&6 to 8&th 2ecem!er %&'6 (%GA o!servations). he data is collected from Bloom!erg

data!ase.

he study uses continuous wavelet transform to e#amine the co$movement of oil price with

(i) nominal e#change rates and (ii) stock indices of ma7or oil$importing countries. he

wavelet coherence is seen as a locali,ed correlation coefficient in the time fre+uency space

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and the relationship is found through the fre+uency !ands and time intervals. = wavelet

transform provides a three$dimensional diagram that illustrates time series information at

different fre+uencies" time and strength. he fre+uency could range from low to high/ the

time could range from short term to long term and finally" the strength of association is

measured !y color coding. 3n this study" we follow ?rinsted et al. (%&&6) framework of

0avelet ransform Coherence (0C). 3nitially" we use Continuous 0avelet ransform(C0) to remove noise in the series and then we use 0C to set the pattern of co$

movement.

. RESULTS AND FINDINGS

.1 D))"$%a%# !& WTI O$' P"$c)#

he analysis using -arkov Switching model at high and low volatile regime shows that

speculative factors have the insignificant role at high$volatile regime !ut is significant at low$volatile regime when controlled for financial and fundamental factors (see a!le '). 2ollar

inde#" 5agged 03 oil price" 1C2 stock" 3ndustrial production of 3ndia" and SEP && plays

a significant role in predicting the changes in crude oil price regardless of the state. he

impact of !asis" 1C2 net imports" 3ndustrial production of China" and 1C2 consumption

on the crude oil is significant in !ullish and !earish market periods !ut it has insignificant

impact in normal market phases. he results indicate that speculation has active role when

com!ined with financial and fundamental factors in high$volatile regime.

Ta5') 1 E&&)c !& #)c('a$), &(%+a)%a' a%+ &$%a%c$a' a"$a5')# !% WTI !$' "$c)

MODEL 1 MODEL 2 MODEL

D))"$%a%# Sa) 1 Sa) 2 Sa) 1 Sa) 2 Sa) 1 Sa) 2

5agged 03 spot oil price &.%&&H $&.'%

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(std. error" p$value)

9oteI HHH '&J significance/ HH J significance/ H 'J significancehe a!le shows results of -arkov Regime Switching -odel for monthly log returns under two regimes low and high.M!+)' 14 )7a$%)# ) )&&)c !& #)c('a$!% !% WTI !$' "$c)8 M!+)' 24 )7a$%)# ) )&&)c !& #)c('a$!% !% WTI !$'

"$c) c!%"!''$%* &!" &$%a%c$a' &ac!"#8 M!+)' 4 )7a$%)# ) )&&)c !& #)c('a$!% !% WTI !$' "$c) c!%"!''$%* &!"

&(%+a)%a' a%+ &$%a%c$a' &ac!"#.

WTI !$' "$c)is valued ; priced in :S K. OPEC "!+(c$!%" OECD %) $!"#and OECD c!%#($!%are measured

as thousand !arrels per day" whereas OECD $%)%!"9 is measured as million !arrels per month. 3ndustrial production ofChina and 3ndia are measured as value in :S K. T"a+) /)$*)+ US D!''a" I%+)7 :B"!a+;4= weighted average of theforeign e#change value of the :.S. dollar against the currencies of a !road group of ma7or :.S. trading partners. Broadcurrency inde# includes the 1uro =rea" Canada" @apan" -e#ico" China" :nited 4ingdom" aiwan" 4orea" Singapore" ong4ong" -alaysia" Bra,il" Swit,erland" hailand" Philippines" =ustralia" 3ndonesia" 3ndia" 3srael" Saudi =ra!ia" Russia"Sweden" =rgentina" >ene,uela" Chile and Colom!ia.12 M!% Ba#$#42ifference !etween spot price and '% month ahead futures price (i.e.) S tL *tM'%. S

RW

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Note: Figure 1.1 & 1. !rese"ts t#e $avelet %o#ere"%y !lot bet$ee" oil !ri%e a"d E%#a"ge rate. 'avelet(s)uared

%o#ere"%ies are i"di%ated by %o"tour, t#e *+ sig"ii%a"%e level is de"oted by a das#ed bla%k li"e %o"tour a"d t#e area

outside t#is li"e is t#e bou"dary ae%ted -o"e. T#e area ae%ted by edge ee%ts are de"oted by t#e %o"e o i"lue"%e a"d t#e

area outside t#e %o"e o i"lue"%e #as "o statisti%al sig"ii%a"%e. T#e %olor %ode or %o#ere"%y ra"ges rom blue %lose to

-ero/ to red %lose to o"e/, $#ere blue reers to lo$ %o#ere"%y a"d red reers to #ig# %o#ere"%y.

!) il price and Stock 3ndicesI

Correlation !etween the stock indices and oil price is high during crisis in short" medium and

long term for the :S stock market inde# (SEP &&) (see figure %.')" 3ndian stock market

inde# (93*)" 4orean stock market inde# (4SP3)" ?erman stock market inde# (2=D 8&)"

*rench stock market inde# (C=C)" Singapore stock market inde# (*SS3)" and Belgium stock

market inde# (B15 %&). igh coherency is witnessed !etween stock indices and oil prices in

the long and medium term for Chinese stock market inde# (SS1 &) (see figure %.%)"

9etherland stock market inde# (=1D)" and 3ndonesian stock market inde# (5F 6). he other

countries indices correlation with oil price is high during crisis only in long term. hose stock

markets include @apan Stock market 3nde# (9ikkei %%)" Spain stock market inde# (3B1D)"

3talian stock market inde# (*S1-3B)" aiwan stock market inde# (0S1)" and urkey

stock market inde# (D: '&&). 2uring crisis" oil price is leading 4SP3" 2=D" 93*" C=C"

3B1D" *SS3" *S1-3B" =1D" 0S1" D: '&&" B15 %&" 5F 6" and 9ikkei %% in the long

term and 93* is leading the oil price in the medium term. 3t is also o!served that in the

long term SEP && is leading the oil price.

FIGURE 2.14 WTI OILV#. SP? FIGURE 2.24 OPEC OIL V#. SSE0

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Note: Figure .1 & . e#ibits t#e $avelet %o#ere"%y !lot or diere"t be"%#mark %rude oil !ri%e a"d sto%k i"di%es o oil

im!orti"g %ou"tries. 0o"te arlo simulatio"s are used to obtai" values or t#e sig"ii%a"%e. 'avelet(s)uared %o#ere"%ies

are i"di%ated by %o"tour, t#e *+ sig"ii%a"%e level is de"oted by a das#ed bla%k li"e %o"tour a"d t#e area outside t#is li"e is

t#e bou"dary ae%ted -o"e. T#e area ae%ted by edge ee%ts are de"oted by t#e %o"e o i"lue"%e a"d t#e area outside t#e

%o"e o i"lue"%e #as "o statisti%al sig"ii%a"%e. T#e %olor %ode or %o#ere"%y ra"ges rom blue %lose to -ero/ to red %lose

to o"e/, $#ere blue reers to lo$ %o#ere"%y a"d red reers to #ig# %o#ere"%y.

6. CONCLUSION

he study e#amines the determinants of crude oil and their impact on the 03 oil price.

-arkov$regime switching methodology was used to analy,e the significance of various

factors in the presence of high$ and low$volatile regimes. ur empirical 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 havesignificant impact on the oil price" whereas at high volatile regimes" only the factors

pertaining to supply" SEP && and trade$weighted :S dollar (Broad) 3nde# have a significant

effect on the oil price. Broadly" the results imply that the effect of speculation on oil price can

only !e seen in low$volatile regimes" whereas" in high$volatile regimes" supply and financial

factors play a significant role in e#plaining the oil price. ur results suggest that regulators

and policymakers should consider supply dynamics while tracking or predicting the

movements of the oil price" particularly" during high$volatile periods.

0avelet Coherence analysis indicates a high coherence !etween oil price and macroeconomic

indicators across all the countries during the financial crisis. he nominal e#change rates tendto have negative relationship with !enchmark oil prices e#cept in the case of e#change rate of

@apan in the long run and e#change rate of South 4orea in the medium run. Stock indices

tend to have positive relationship with !enchmark oil prices in !oth long and medium run.

SEP is leading the oil price" whereas SS1&" 9ikkei %%" 93*" 4PS3" 2=D" C=C"

3B1D" *SS3" *S1-3B" =1D" 0S1" D: '&&" 5F6 and B15 %& are lagging the oil price

in the long run. 3n the medium term" e#cept for 93*" oil price is leading the stock market

inde#. verall" the results indicate that the oil price and stock indices of ma7or oil$importing

countries are correlated in long and medium term" !ut not in short term. he leadLlag

relationship !etween oil price and macroeconomic indicators are o!served to change acrossfre+uency and time. 0hile e#change rate offers diversification !enefits" stock market indices

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provide no diversification avenues since the pattern of co$movement of stock market indices

and oil prices are similar across all oil importing countries.

@. CONTRIBUTIONS OF THE STUDY

ur study contri!utes to the oil price determinants literature in the following waysI

a. 0e contri!ute !y e#amining the impact of speculative activity in derivative

segment on 03 crude oil prices" controlling for fundamental factors and

financial factors.

!. 0e contri!ute !y considering individual demand factors such as 1C2

consumption" 1C2 net import and supply factors such as P1C production"

1C2 inventory and also account for increasing demand from emerging

economies.

c. 0e contri!ute methodologically !y using -arkov Regime Switching

methodology to control for structural !reak and non$linearity. 0e also develop

a multivariate framework to e#amine the impact of fundamental" financial and

speculative factors on oil prices at high and low volatility regime.

0ith respect to comovement dynamics of oil prices with macro factorsI

d. 1#isting literature focused more on real prices (iwari et al." %&'8/ Benhmad"

%&'%). 0e use nominal prices of oil instead of real prices" and there!y ena!le

investors to shift their positions +uickly in stock and fore# market to mitigate

the risk arising from volatility in oil prices.

e. 0hile previous studies have focused only 03 crude" different crude oil

!enchmarks such as 03" Brent and P1C have !een used to e#amine the

comovement dynamics. he P1C !asket crude is used for =sian countries/

Brent oil price is used for 1urope and 03 oil price is used for the :S.

f. Previous literature e#tensively focuses on time series methodologies to

measure co$movement" !ut we study the relationship !etween the crude oil

and macroeconomic indicators !oth at time and fre+uency domain using

wavelet coherence techni+ue.

. IMPLICATIONS OF THE STUDY

Policymakers" regulators and investors can incorporate speculative factors while predicting

oil price movement during volatile period" since the speculative factors are found to have

significant impact on crude oil price" alongwith financial and fundamental factors in high$

volatile regimes. he long$term correlation !etween the oil price and macro$economic factors

implies that oil price can !e determined using the lag of e#change rate and stock inde# can !e

estimated using the oil price lags. he results have implications for individual traders and

institutional investors while designing their portfolio for short" medium and long term time

hori,ons.

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. LIMITATIONS

(') >arious determinants of oil prices were incorporated into the model to see how

speculative varia!les !ehave with respect to other determinants such as fundamental

and financial factors. 0hile political factors such as type of ?overnment (democracy"

monarchy etcN) and type of economy (open economy" closed economy etcN) mayplay a key role in determination of the oil prices" we discontinued these factors due to

nonavaila!ility of data and am!iguity in measurement.(%) he short$run relationships in wavelet coherence analysis were not captured due to

high fre+uency daily data. But using weekly or monthly data could !etter visuali,e the

short$run movements or relationship !etween varia!les. -oreover" the co$movement

analyses was limited to only two macrofactors such as e#change rate and stock inde#

and other factors were not considered.

10. SCOPE FOR FUTURE RESEARCH

i. =symmetric effect of crude oil on macroeconomic varia!les could provide a !etter

understanding on the correlation !etween the oil price and macroeconomic varia!les.

ii. Co$movement of oil prices is o!served only for the stock indices and e#change rate.

he correlation with other macroeconomic varia!les such as interest rate and inflation

with the oil price might provide more insight on fluctuations in the crude oil prices.

REFERENCES

Basher" S. =." aug" =. =." E Sadorsky" P. (%&'%). il prices" e#change rates andemerging stock markets. E"ergy E%o"omi%s" 23(')" %%GL%6&.httpI;;doi.org;'&.'&'A;7.eneco.%&''.'&.&&.

Basher" S. =." E Sadorsky" P. (%&&A). il price risk and emerging stock markets. 4lobalFi"a"%e 5our"al" 16(%)" %%6L%'. httpI;;doi.org;'&.'&'A;7.gf7.%&&A.&6.&&'.

Beckmann" @." E C,uda7" R. (%&'8). il prices and effective dollar e#change rates.I"ter"atio"al 7evie$ o E%o"omi%s a"d Fi"a"%e" 6" A%'LA8A.httpI;;doi.org;'&.'&'A;7.iref.%&'%.'%.&&%.

Benhmad" *. (%&'%). -odeling nonlinear ?ranger causality !etween the oil price and :.S.

dollarI = wavelet !ased approach. E%o"omi% 0odelli"g" 8(6)" '&L''6.httpI;;doi.org;'&.'&'A;7.econmod.%&'%.&'.&&8 .

Breitenfellner" =." Cuaresma" @." E 4eppel" C. (%&&). 2eterminants of Crude il PricesISupply" 2emand" Cartel or SpeculationO 0o"et 9oli%y E%o" " 3" '''L'8A. Retrievedfrom httpI;;www.national!ank.at;en;img;mop%&&+6analyses&Atcm'A$'

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Cong" R. ?." 0ei" . -." @iao" @. 5." E *an" . (%&&

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riavwote" >. 1." E 1riemo" 9. . (%&'%). il prices and the real e#change rate in9igeria.I"ter"atio"al 5our"al o E%o"omi%s a"d Fi"a"%e" 3(A)" '

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CHAPTER 1 INTRODUCTION

'.' -a7or oil price shocks

'.% 2eterminants of crude oil

'.8 3nter$relationship !etween crude oil and macro economy

'.6 9eed for the study

'. !7ectives of study

'.A ypothesis

'.G 2ata and sample

'.< -easurement of varia!les

'. -ethodology

'.'& utline of the thesis

CHAPTER 2 DETERMINANTS OF OIL PRICE4 A MAR>OV REGIME

SWITCHING APPROACH

%.' 3mportance of oil price determinants

%.% 5iterature on factors influencing oil price

%.8 *ramework of the study

%.6 2ata and sample

%. -ethodology

%.A 2eterminants of 03 oil price

%.A.' est for non$linearity

%.A.% 1ffect of speculation on oil price

%.A.8 1ffect of speculation on oil price controlling for financial factors

%.A.6 Relative importance of determinants of oil price

CHAPTER WAVELET DYNAMICS OF OIL PRICE, E?CHANGE RATE AND

STOC> INDE?

8.' 3ntroduction

8.% 5iterature review

8.8 Conceptual framework

8.6 2ata and sample

8. -ethodology

8..' Continous wavelet transform

8..% 0avelet coherence (0C)

8.A 0avelet dynamics of oil price and e#change rate

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8.G 0avelet dynamics of oil price and stock inde#

CHAPTER 3CONCLUSION

6.' *indings of the study

6.%.Contri!utions of the study6.8.3mplicationsof the study

6.6. 5imitations of the study

6. Scope for future work

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