Determinants of Stock Market Co-Movements between Pakistan and Asian Emerging Economies

14 Pages·2017·0.22 MB·English

Journal of
Risk and Financial
Management
Article
Determinants of Stock Market Co-Movements
between Pakistan and Asian Emerging Economies
MuhammadAamir*andSyedZulfiqarAliShah
FacultyofManagementStudies,InternationalIslamicUniversity,Islamabad44000,Pakistan;
zulfi[email protected]
* Correspondence:[email protected];Tel.:[phone]
(cid:1)(cid:2)(cid:3)(cid:1)(cid:4)(cid:5)(cid:6)(cid:7)(cid:8)(cid:1)
(cid:1)(cid:2)(cid:3)(cid:4)(cid:5)(cid:6)(cid:7)
Received:29May2018;Accepted:8June2018;Published:21June2018
Abstract: Thisstudyanalyzesthedeterminantsofstockmarketco-movementbetweenPakistanand
Asianemergingeconomiesfortheperiod2001to2015. AugmentedDickeyandFuller(ADF)and
Philips-Perron(PP)testsareappliedtocheckco-integrationbetweentheirstockmarkets. Results
ofthisstudyrevealthatthereislong-termintegrationbetweenthestockmarketofPakistanand
the stock markets of China, India, Indonesia, Korea, Malaysia and Thailand. This study reports
thedrivingforcesoftheco-movementbetweenthePakistanandAsianemergingmarketswhere
co-integrationisfound. Resultsofthepaneldatarevealthattherearesignificantunderlyingforcesof
integrationbetweenPakistanandeachAsianemergingstockmarket. Thefindingsofthisstudyhave
significantimplicationsforpolicymakersinPakistanwhoaredesigningstrategiesformacroeconomic
harmonizationandstabilityofthecountry’seconomyagainstfinancialshocks.
Keywords:stockmarketco-movement;portfoliodiversification;economicintegration;financialcrisis
1. Introduction
The consequences of the financial crisis (2007–2010) resulted in unexpected and immediate
deterioration of wealth. The after-effects of the global financial storm are still evident and nearly
allcountriescontinuetosufferasaresult. TheWorldBankhascurrentlyadvisedtheG20nations
of the occurrence of an extremely critical and damaging economic meltdown in the near future.
As latest literature proposes, examining the tendency of one country to be affected by the global
financialstormhelpspreventfuturecrisis. Thisfeaturehasattractedtheattentionofacademicians
andpractitionerstowardstheidentificationoftheintegrationanddeterminationoffundamentalsthat
mightdescribehowstockmarketsofdifferentcountriesarecorrelatedtoeachother(Pretorius2002).
Suchriseofinterestsandinspirationscanbedescribedforseveralreasons,butthemostappropriate
ofallincludesthequestforlikelybenefitsofriskmanagement, especiallyportfoliodiversification
(ForbesandChinn2004).
There has been a substantial increase in economic and financial linkages among economies.
The main causes of these strong linkages between global economies are technological advances,
removal of statutory controls, market liberalization and the growth of several emerging markets.
Thesefactorshavecontributedtomoreinterlinkedeconomies,whichinturnaresaidtohavegiven
risetoahigherdegreeofstockmarketco-movement(JohnsonandSoenen2003). Theintegrationof
emergingstockmarketsremainsanopenquestionthathasnotbeenadequatelyaddressed. Modern
research in stock market integration has not focused enough on the determinants of stock market
co-movement. Ithasbeenfoundthatveryfewstudieshaveattemptedtouncoverthedeterminantsof
stockmarketco-movement.
J.RiskFinancialManag.2018,11,32;doi:10.3390/jrfm11030032 www.mdpi.com/journal/jrfm
J.RiskFinancialManag.2018,11,32 2of14
1.1. StockMarketCo-Movement
Stock market co-movement refers to a tendency of two or more stock markets to move
simultaneously, so that their price movements are positively correlated. National stock markets
areconsideredtobeintegratedifsecuritieswithsimilarriskfeaturesarepricedthesame,evenifthe
securitiesaretradedindifferentstockmarkets(MarashdehandShrestha2010). Putdifferently,stock
marketintegrationisasituationwherefinancialsecuritieshavesimilarityinreturnpatterns.
1.2. TheoreticalFramework
The overarching theory of research study is the Theory of Stock Market Co-movement. This
theoryprimarilyfocusesontwoleadingapproaches(ForbesandRigobon2002). Oneiscalled‘theories
ofnon-contingentcrisis’(fundamentalapproach)andthesecondistermed‘theoriesofcontingent
crisis’(behavioralapproach).
1.2.1. TheoriesofNon-ContingentCrisis
Thistheoryassumesthattransmissionmechanismafteracrisisisnotsignificantlydissimilarto
thosebeforethecrisis.Accordingtothetheoryofnon-contingentcrisis,excessiveco-movementsoftwo
differentmarketsareduetothecontinuationofcrisislinkages. Thisisoftentermedasfundamental
approach. Excessiveco-movements,inthiscase,istherepercussionofstrongbilateraltrade,financial
linksandeconomicinterdependence(ForbesandRigobon2002).
Accordingtothefundamentalapproach,thelatestliteratureclassifiesfundamentaldrivingforces
ofco-movementsbetweenstockmarketsasmacroeconomic(bilateraltrade,interestrate,inflationrate,
industrialproductiongrowth,absolutechangesinthebilateralexchangerate,volatilityinthebilateral
exchangerate),andfinancial(nationalequitymarketsize,volatilityacrosstheworldstockmarket).
InternationalCapitalGoodsTradeHypothesis
Thehypothesisstatesthateconomiesaswellasstockmarketsoftwocountriesareanticipatedto
behighlyintegratedduetotheirstrongbilateraltraderelationship. Thestrongerthebilateraltrade
relationship,thehigherthelevelofco-movementbetweenstockmarketswillbe. Thus,theextentof
bilateraltradebetweentwodifferentcountriesisexpectedtoexplainco-movementbetweenthestock
marketsofthesecountries.
DiscountedCashFlowModel(ConvergenceofMacroeconomicVariables)
Thediscountedcashflowmodelstatesthatsimilaritiesinthemacroeconomicvariablesofthetwo
differentcountrieswillleadtosimilaritiesintheperformanceoftheirstockmarkets. Putdifferently,
convergence of macroeconomic variables will lead to convergence in stock market performance.
Onthecontrary,divergenceofmacroeconomicvariables,intheformoflargerdifferentials,willlead
todivergenceinstockmarketperformance. Forexample,largerdifferentialsininterestrate,growth
rateandinflationrateswillcausealowerlevelofco-movement.
FlowOrientedHypothesisofExchangeRateDetermination
Thegreaterthevolatilityintheexchangerate,thegreaterwillbetheuncertaintyintheeconomy
aswellasintheintegrationofstockmarkets.Consequently,volatilityintheexchangeratemustshowa
negativeassociationwiththeco-movementsofstockmarkets. Similarly,alargerexchangeratechange
willbringmorebenefittothecountrywiththedepreciatingcurrency. Therefore,therateofchangein
theexchangeratemustshowanegativeassociationwithstockmarketco-movement.
1.3. ResearchGap
Thefollowingresearchgapsaredealtwithinthisstudy:
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(1) TheintegrationofAsianemergingmarketsremainsanopenquestionthathasnotbeenadequately
addressed(Dhanarajetal.2017).
(2) Modernresearchinstockmarketintegrationhasnotadequatelystudiedthedrivingforcesof
stockmarketco-movement,especiallyinAsiaandinIslamicemergingeconomies(Karimand
Majid2017).
(3) Existing research on stock market co-movement has not adequately focused on whether the
extent of bilateral trade between two different countries is expected to explain co-movement
betweenthestockmarketsofthesecountries(Mobareketal.2016).
(4) Existing research on stock market co-movement has not adequately focused on whether or
notthesimilarityinmacroeconomicvariablesbetweenemergingeconomieswillresultinthe
co-movementbetweenthesecountries(Mobareketal.2016).
(5) Currentresearchonstockmarketco-movementhasnotadequatelyfocusedonwhetherornot
thevolatilityinthebilateralexchangerateandabsolutechangesinthebilateralexchangerate
betweenemergingeconomieswillresultstockmarketco-movementbetweenthesecountries
(Mobareketal.2016).
1.4. ResearchQuestions
Thefollowingresearchquestionsaredealtwithinthisstudy:
(1) Arefinancialmarketsco-integrated?
(2) Whetherornotthesimilarityinmacro-economicvariablesbetweentwodifferentcountrieswill
resultinhigherlevelsofstockmarketco-movement
(3) Whetherornotstrongerbilateraltraderelationshipbetweentwodifferentcountrieswillresultin
higherlevelsofstockmarketco-movement
(4) Whetherornotgreaterabsolutechangesinthebilateralexchangeratewillresultinhigherlevels
ofstockmarketco-movement
(5) Whetherornotgreatervolatilityinthebilateralexchangeratewillresultinhigherlevelsofstock
marketco-movement
(6) Whether or not the volatility in the world stock market will result in higher levels of stock
marketco-movement
2. LiteratureReview
The existing literature presents numerous studies that show the existence of stock market
interdependence, withtheideathatstockmarketshavebeenshowingtighterco-movementswith
eachother. Academicliteratureallotsthisincreasedlevelofstockmarketintegrationtodevelopment
inclosereconomicandfinanciallinkages. However, itisobviousthatveryfewstudieshavebeen
conductedonthedeterminantsofstockmarketco-movement,whichmakesitaninterestingresearch
area. Consequently, attention is directed towards research on the nature of links that lead the
interdependenceofinternationalstockmarkets. Cantheextentofintegrationbeexplainedbythe
fundamentaldeterminants? Inotherwords,eithertheco-movementofstockmarketsiscontagionin
realityorcanitbeclarifiedbyeconomicorfinancialfundamentals?
2.1. EmpiricalStudiesShowingtheCrossMarketCo-Movement
Recently,resultsofdifferentstudiesonstockmarketinterdependencerevealasubstantialdegree
ofintegration(Mobareketal.2016). AlNasserandHajilee(2016)studiedstockmarketintegration
amongemergingeconomies(Brazil,China,Mexico,Russia,andTurkey)anddevelopedeconomies
(U.S.,U.K.andGermany). ResultsoftheARDLmodelrevealedthatshort-termintegrationisfound
betweenthestockmarketsofgrowinganddevelopedcountries. Itwasfurtherreportedthatonlythe
GermanstockmarketisintegratedwithBrazil,China,Mexico,RussiaandTurkey.
J.RiskFinancialManag.2018,11,32 4of14
Bashiri and Zadeh (2014) examined the interdependence between stock markets of Malaysia,
Indonesia,Philippines,Japan,TurkeyandthoseintheU.S.byusingmonthlydatafortheperiodof
1995to2010. ResultsrevealedthatintegrationisfoundbetweenU.S.andAsianstockmarkets. Itwas
furtherreportedthattheextentofintegrationbetweenJapanandotherAsianmarketsislow.Inanother
study conductedby Deltuvait(2015), theintegration of theBaltic stock markets was examinedby
applyingcross-correlationanalysis,Grangercausalitytest. Resultsofdifferenttechniquesshowedthe
higherintegrationofLithuanianandEstonianstockmarkets.
RuaandLuis(2009)examinedco-movementinthetime–frequencyspacebyapplyingthewavelet
analysis. Resultsofthestudyemphasizethesignificanceoftakingintoaccountthetimeandfrequency
varyingpropertiesofstockreturnsco-movementindesigningportfoliosattheinternationallevel.
2.2. EmpiricalEvidencesofDeterminantsofStockMarketCo-Movement
KarimandMajid(2017)examinedthefundamentaldrivingforcesofintegrationamong10Islamic
stockmarketsbyapplyingPooledOLSandfoundthatallvariablesareinsignificantindescribing
theintegration. ResultsofthepaneldataestimationhavefoundthatonlyGDPgrowthdifferential
andinflationdifferentialaresignificantinexplainingtheco-movementbetweenthestockmarkets
ofIslamiccountries. Anotherstudyrelatedtothedrivingforcesofstockmarketco-movementwas
conductedbyMobareketal. (2016)andreportedthatimportdependenceaswellassizedifferential
ofstockmarketsaresignificantinexplainingtheco-movementbetweenthereturnsofstockmarkets.
Inadditiontothesedeterminants,GDPgrowthratedifferentialandtimetrendalsohasasignificant
relationshipwiththeco-movementofstockmarket.
GuesmiandTeulon(2014)examinedtheunderlyingforcesofstockmarketintegrationofMiddle
Eastcountries(Turkey,Israel,JordanandEgypt). Theresultsrevealedthatdomestic(inflation,rateof
spreadvariationandexchangeratevolatility)andglobal(globalinterestrate,worldmarketreturns,
andworldmarketdividendyields)factorsaresignificantinexplainingtheintegrationbetweenthe
stockmarketsofMiddleEastcountries.
Narayanetal.(2014)examinedtheintegrationofstockmarketsamongemergingAsianeconomies
anddevelopedmarketsbyapplyingtheEGARCH-dynamicconditionalcorrelations(DCC).Resultsof
thestudyrevealedstrongcorrelationsduringtheperiodoffinancialcrisis. Resultsfurtherreported
thatpricedifferentials,exchangeraterisk,globalfinancialcrisis,bilateraltraderelations,openness
variableanddomesticmarketcharacteristicsareunderlyingforcesofstockmarketintegration.
Contrary to the above, Kose et al. (2003) found that results do not support the hypothesis
that bilateral trade and stock market co-movement have a positive relationship. A research work
byBrackeretal. (1999)analyzedthedrivingforcesofstockmarketco-movementandreportedthat
numerousfactorslikebilateraltradeandsizedifferentialsoftwomarketsarenotablylinkedwiththe
degreeoftheco-movement.Inaddition,atimetrendandregionaldummyvariablewasalsosignificant
inexplainingtheco-movementbetweenthereturnsoftwostockmarkets.
Pretorius(2002)studiedthedrivingforcesofco-movementbetweenstockmarketsandfoundthat
significant results were observed between the bilateral trade and the stock market co-movement.
In addition, industrial production growth differential was also significant in describing the
co-movement between stock markets of two countries. Another study related to bilateral trade
andstockmarketco-movementwasconductedbyJohnsonandSoenen(2003)andfoundthattradeis
significantlycorrelatedwiththedegreeofstockmarketco-movementovertime.
BrackerandKoch(1999)suggestedthattheextentofstockmarketco-movementisdependent
on the extent of economic integration between two countries. Put differently, if the two countries
havestrongeconomicintegration,thentheymusthaveagreaterco-movementintheirstockmarkets.
Theresultspointoutthattheextentofstockmarketco-movement(measuredasthemagnitudeofthe
correlationstructure)ispositivelyassociatedwithtrendandvolatilityintheworldmarket. Inaddition,
theextentofstockmarketintegrationhasanegativeassociationwithvolatilityinbilateralexchange
rate,realinterestratedifferentials,termstructuredifferentialsandreturnonaworldmarketindex.
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LinandCheng(2008)analyzedthedrivingforcesofthestockmarketco-movementandreported
thatvolatilityinthestockmarket,interestratedifferentials,andtherateofchangeinexchangerateare
significantinexplainingtheco-movementbetweenthereturnsofstockmarkets.
2.3. Hypothesis
Hypothesis1. Thereisco-movementbetweenthestockmarketsoftwocountries.
Hypothesis2. Thegreater(lesser)thedivergencebetweeninterestratedifferentials, thelower(higher)the
co-movementbetweenthestockmarketswillbe.
Hypothesis3. Thegreater(lesser)thedivergencebetweeninflationratedifferentials,thelower(higher)the
co-movementbetweenthestockmarketswillbe.
Hypothesis 4. The greater (lesser) the divergence between industrial production growth rate differentials,
thelower(higher)theco-movementbetweenthestockmarketswillbe.
Hypothesis5. Thegreater(lesser)thedivergencebetweenGDPgrowthratedifferentials,thelower(higher)the
co-movementbetweenthestockmarketswillbe.
Hypothesis6. Thegreater(lesser)theabsolutechangesinthebilateralexchangerate,thelower(higher)the
co-movementbetweenthestockmarketswillbe.
Hypothesis 7. The greater (lesser) the volatility in the bilateral exchange rate, the lower (higher) the
co-movementbetweenthestockmarketswillbe.
Hypothesis8. Thegreaterthevolatilityintheworldequitymarket,thegreatertheco-movementbetweenthe
stockmarketswillbe.
Hypothesis9. Thestrongerthebilateraltradetiesbetweenthetwocountries, thehighertheco-movement
betweenthestockmarketswillbe.
3. ResearchMethodology
3.1. Sample
The purposive sample consists of Asian emerging economies by the MSCI Global Investable
MarketIndices. Table1showstheindicesusedforAsianstockmarkets.
Table1.DescriptionofIndices.
Country StockMarketIndex Country StockMarketIndex
China SHASHRindex Malaysia FBMKLCIindex
India NIFTYindex Pakistan KSE100index
Indonesia IDXcompositeindex Philippine PSEIindex
Korea KOSPIindex Thailand SEIindex
3.2. SamplePeriod
Thestudyperiodisfrom1January2001to31December2015andincludestheglobalfinancial
crisis that started suddenly in U.S. financial institutions in 2007 and escalated to other developed
countriesinthefirstsixmonthsoftheyear2008.
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3.3. DataCollection
DailydataofdifferentemergingstockindiceswascollectedfromtheDataStream. Dailydatawas
selectedtoevadetheincorrectcorrelationproblem(PatraandPoshakwale2006). Tomanagemissing
data,Occam’srazortechniqueisusedinthisstudybyfillinginthelastdaypriceofthestockmarket
(Majidetal.2009;HirayamaandTsutsui1998). Secondarydataforthedeterminantsofstockmarket
co-movement was collected from Data Stream, State Bank of Pakistan, World Bank, KSE website,
andtradingeconomicswebsite.
3.4. VariablesofStudy
3.4.1. CorrelationbetweenCountryiandj(Cor )
ij
Correlationbetweendailyrateofreturnofcountriesiandjduringquartert.
3.4.2. BilateralTrade
Thesumofthevalueofbilateraltradeasaproportionofeachcountry’stotaltradeisused.
X +M X +M
ij ij ji ji
Trade = + (1)
ij X +M X +M
i i j j
whereX and M istheexportsandimportsfromcountryitocountryj. X and M isthetotalexport
ij ij i i
andtotalimportofcountryi.
3.4.3. ConvergenceofMacroeconomicVariables
Asdirectionofcausalityisnotinvolvedincaseofcorrelation,itisimportanttousetheabsolute
value of the interest rate differential, inflation rate differential, GDP growth rate differential and
industrialproductiongrowthratedifferential.
3.4.4. AbsoluteChangeintheBilateralExchangeRate
Percentchangeinbilateralexchangerateduringquartertiscalculatedbysuggestingapossible
indirectnegativerelationshipbetweentheabsoluteexchangeratechangesandtheco-movementof
thetwostockmarkets.
3.4.5. VolatilityintheBilateralExchangeRate
Standarddeviationindailybilateralexchangerateduringquartertiscalculatedforvolatility
inthebilateralexchangerate,suggestingthatthegreatertheexchangeratevolatility,thelowerthe
co-movementbetweenthestockmarketswillbe.
3.4.6. WorldMarketVolatility
Standarddeviationofdailyworldstockmarketindexreturninquartertiscalculatedforvolatility
intheworldmarket,suggestingapositiveassociationbetweenthevolatilityintheworldmarketand
theco-movementofthestockmarkets.
3.5. EconometricModelforFundamentalDeterminantsofStockMarketCo-Movement
Thefinalregressionmodelincorporatesallofthedeterminantsmentionedasearlier:
Cor =β +β |Int −Int| +β |Inf −Inf| +β |Ind −Ind| +β |Gdp−Gdp| +
ij 0 1 i j t 2 i j t 3 i j t 4 j t
β TRADE +β |XRCH | +β XRSD +β WMV +ε
5 ijt 6 ij t 7 ijt 8 t ijt
Cor =Estimatedcorrelationbetweendailyreturnsincountriesiandjduringquartert.
ij
ε =disturbanceterm,assumedtobeiidN(0,σ2).
ijt
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Int =Interestrateincountryiduringquartert.
it
Inf =Inflationrateincountryiduringquartert.
it
Ind =Industrialproductiongrowthrateincountryiduringquartert.
it
Gdp =GDPgrowthrateincountryiduringquartert.
it
XRCH =Percentchangeinbilateralexchangerateduringquartert.
ijt
XRSD =Standarddeviationindailybilateralexchangerateduringquartert.
ijt
WMV =Standarddeviationofdailyworldstockmarketindexreturnduringquartert.
t
4. ResultsofStockMarketIntegration(LongTermIntegration)
Descriptive statistics for stock returns, unit root tests and co-integration test of data period
2001–2015arepresentedinthetablesbelow.
4.1. DescriptiveStatistics
Table2presentsdescriptivestatisticsfordailystockmarketreturns. Wenotethatallemerging
stockmarketspostedpositiveaverageperformanceduringthetimeperiod. Weexaminethevolatility
ofallcountriesmarketreturns. Ithasbeenreportedinmodernliteraturethatvolatilityisusuallyfound
inemergingstockmarkets. ThestockindexforKoreashowsthemaximumvolatilityamongallthe
stockreturns. ThestockindexforMalaysiashowstheminimumvolatilityamongallthestockreturns.
Table2.DescriptiveStatisticsforAsianStockMarketReturns.
Variable Mean Median Maximum Minimum Std.Dev
China 0.000 0.000 0.321 −0.168 0.017
India 0.000 0.000 0.162 −0.120 0.015
Indonesia 0.000 0.000 0.140 −0.119 0.015
Korea 0.000 0.000 0.119 −0.120 0.017
Malaysia 0.000 0.000 0.231 −0.214 0.013
Pakistan 0.000 0.000 0.136 −0.123 0.015
Philippines 0.000 0.000 0.175 −0.122 0.014
Thailand 0.000 0.000 0.120 −0.148 0.015
4.2. UnitRootTest
Table3showsthatallemergingstockmarketindicesareintegratedoforderone,I(1). Results
oftheADFtestareherebyconfirmedbythePhilips-Perrontest.Asaresult, wecanmovetowards
co-integrationanalysis,examiningifthereisalong-runrelationshipbetweenPakistanandselected
emergingstockmarketsornot.
Table3.ResultsofAugmentedDickeyFullerTestandPhilips-PerronTest.
LevelADFTest 1stDifference LevelPPTest 1stDifferencePP
Countries
Statistics ADFTestStatistics Statistics TestStatistics
China −1.827 −71.29* −1.836 −71.295*
India 0.142 −65.449* −0.104 −65.984*
Indonesia 0.105 −62.430* −0.012 −62.314*
Korea −1.029 −68.351* −1.075 −68.250*
Malaysia −0.852 −68.422* −0.940 −68.441*
Pakistan 0.733 −66.220* 0.307 −68.093*
Philippines 0.048 −62.009* −0.119 −61.872*
Thailand −0.981 −66.887* −1.110 −67.088*
Note:*indicatesthatADFstatisticsandPPstatisticsaresignificantforthefirstdifferenceofallstockindicesat5%
levelofsignificance.
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ItcanbeseeninTable3thatallthevariablesareintegratedofthesameorderi.e.,I(1)stationary
at1stdifference.
4.3. Co-IntegrationTests
ResultsofpairwiseJohansenandJuseliusco-integrationtestsarereportedinTable4. Theyreveal
that there is long-term integration between the stock market of Pakistan and the stock markets of
China,India,Indonesia,Korea,Malaysia,ThailandandTurkey,ascriticalvaluedonotexceedthetrace
statisticsat5%levelofsignificance.
Table4.ResultsofCo-integrationTests.
No.ofHypothesized TraceTest MaximumEigenValueTest
Country
CE(s) TestStat Crit.Value TestStat Crit.Value
None 14.093 18.397 8.729 17.147
China
AtMost1 5.3643 3.841 5.364 3.841
None 16.792 18.397 11.189 17.147
India
AtMost1 5.6030 3.841 5.603 3.841
None 11.001 18.397 5.964 17.147
Indonesia
AtMost1 5.0374 3.841 5.037 3.841
None 18.064 18.397 10.842 17.147
Korea
AtMost1 7.2225 3.841 7.222 3.841
None 11.177 18.397 6.638 17.147
Malaysia
AtMost1 4.5390 3.841 4.539 3.841
None 8.1399 18.397 5.693 17.147
Philippines
AtMost1 2.446 3.841 2.446 3.841
None 13.316 18.397 8.377 17.147
Thailand
AtMost1 4.939 3.841 4.939 3.841
5. CountryWiseDeterminantsofStockMarketCo-MovementbetweenPakistanandAsian
EmergingEconomies
5.1. PakistanandChina
Determinantsofstockmarketco-movementbetweenPakistanandChinaarereportedinTable5.
ThecoefficientestimateforthevolatilityinthebilateralexchangeratebetweenPakistanandChinais
significantandnegative. SuchresultsareinlinewithBrackeretal. (1999),LinandCheng(2008). They
reportthatvolatilityinthebilateralexchangerateissignificantandnegativelyassociatedwithstock
marketco-movement. Inotherwords,greatervolatilityinthebilateralexchangeratebetweenPakistan
andChinaresultsinlowerco-movementbetweentheirstockmarkets. Thecoefficientestimateforthe
worldmarketvolatilitybetweenPakistanandChinaissignificantandpositive. Suchresultsareinline
withtheearlierresearchworkofBrackerandKoch(1999).Puttingitdifferently,worldmarketvolatility
ispositiveandsignificantinexplainingthecorrelationbetweentwostockmarkets. Theco-efficient
estimateforthegdpgrowthrate,industrialproductiongrowthrate,inflationrateandinterestrate
betweenPakistanandChinaisinsignificantandwillthereforehavenoeffectonthereturnsofthetwo
stockmarkets. TheR-squareof0.308indicatesthat30.8%ofthevariationinthecorrelationcoefficients
isexplainedbythevariablesunderstudy,whichisindicationofareasonablygoodfit.
J.RiskFinancialManag.2018,11,32 9of14
Table5.DeterminantsofStockMarketCo-movementbetweenPakistanandChina.
Variable Coefficient Std.Error t-Statistic Prob
C −0.176 0.179 −0.984 0.331
Tradeijt 0.003 0.002 1.182 0.244
GDP 0.002 0.025 0.090 0.928
IND 0.000 0.002 0.320 0.750
INF −0.009 0.007 −1.247 0.219
INT 0.010 0.017 0.582 0.563
WLDVOL 0.003 0.001 2.513 0.016
XRCH −5.727 2.689 −2.129 0.039
XRSD −1.364 0.453 −3.010 0.004
R-squared 0.308
Prob(F-statistic) 0.065
5.2. PakistanandIndia
Determinantsofstockmarketco-movementbetweenPakistanandIndiaarereportedinTable6.
The coefficient estimate for bilateral trade between Pakistan and India is significant and positive,
showingthatbilateraltradeissignificantinexplainingthecorrelationbetweenPakistanandIndia.
SuchresultsareinlinewithBekaertandHarvey(1997),Brackeretal.(1999),JohnsonandSoenen(2003),
Pretorius(2002),andWalti(2005). Theyreportthattradeissignificantlyandpositivelyassociated
withstockmarketco-movement. Inaddition,ourresultsareinlinewithForbesandChinn(2004),
LuceyandZhang(2010). Theyreportthattheextentofstockmarketco-movementisdependentonthe
extentofstrongbilateraltraderelationships. Puttingitdifferently,strongerbilateraltradetiesbetween
PakistanandIndiaresultinhigherco-movementbetweentheirstockmarkets.
Table6.DeterminantofStockMarketCo-movementbetweenPakistanandIndia.
Variable Coefficient Std.Error t-Statistic Prob
C −0.089 0.110 −0.808 0.423
Tradeijt 0.134 0.063 2.122 0.040
GDP −0.026 0.014 −1.859 0.0709
IND 0.003 0.002 1.628 0.111
INF −0.032 0.019 −1.604 0.117
INT −0.024 0.008 −2.749 0.009
WLDVOL 0.005 0.002 2.456 0.018
XRCH −2.136 3.051 −0.700 0.488
XRSD 3.526 3.043 1.158 0.254
R-squared 0.223
Prob(F-statistic) 0.259
ThecoefficientestimatefortheinterestratedifferentialbetweenPakistanandIndiaissignificant
andnegative. TheresultsofthisstudyarealsoinlinewithBrackerandKoch(1999), Brackeretal.
(1999), and Lin and Cheng (2008). They report that interest rate differential of two countries
is significantly and negatively associated with the co-movement of stock markets. Putting it
differently,smallerinterestratedifferentialpromotestheintegrationofstockmarketsoftwocountries.
Thecoefficientestimateforgdpgrowthrate,industrialproductiongrowthrate,inflationrate,world
marketvolatility,absolutechangeinthebilateralexchangerateandvolatilityinthebilateralexchange
rateisinsignificantandwillhavenoinfluenceonthepricesandreturnsofthestockmarketsofPakistan
andIndia. TheRsquareof0.223indicatesthat22.3%ofthevariationinthecorrelationcoefficients
isexplainedbythevariablesunderstudyandalsoindicatethepresenceofothervariablesaffecting
thecorrelation.
J.RiskFinancialManag.2018,11,32 10of14
5.3. PakistanandIndonesia
Determinants of stock market co-movement between Pakistan and Indonesia are reported
in Table 7. The coefficient estimate for the world market volatility between Pakistan and
Indonesia is significant and positive. Such results are consistent with previous research work
like BrackerandKoch(1999). In other words, world market volatility is positive and significant
in explaining the correlation between the two stock markets. The R-square of 0.248 indicates that
24.8%ofthevariationinthecorrelationcoefficientsisexplainedbythevariablesunderstudyand
alsoindicatethepresenceofothervariablesaffectingthecorrelation. Thecoefficientestimateforthe
bilateraltrade,gdpgrowthrate,industrialproductiongrowthrate,inflationrate,interestrate,absolute
changeinthebilateralexchangerateandvolatilityinthebilateralexchangerateisinsignificantand
willhavenoinfluenceonthepricesandreturnsofthestockmarketsofPakistanandIndonesia.
Table7.DeterminantofStockMarketCo-movementbetweenPakistanandIndonesia.
Variable Coefficient Std.Error t-Statistic Prob
C −0.077 0.104 −0.736 0.466
Tradeijt 0.072 0.106 0.680 0.500
GDP −0.008 0.008 −1.048 0.301
IND 0.000 0.002 0.178 0.859
INF −0.010 0.006 −1.448 0.156
INT 0.016 0.010 1.543 0.131
WLDVOL 0.004 0.002 2.158 0.037
XRCH −0.301 2.902 −0.103 0.918
XRSD −406.136 795.639 −0.510 0.612
R-squared 0.248
Prob(F-statistic) 0.181
5.4. PakistanandKorea
Determinantsofstockmarketco-movementbetweenPakistanandKoreaarereportedinTable8.
ThecoefficientestimatefortheGDPgrowthratedifferentialbetweenPakistanandKoreaissignificant
andnegative,showingthatthelowerGDPgrowthratedifferencebetweenPakistanandKorearesults
inhigherco-movement. SuchresultsareinlinewiththeresultsofearlierstudieslikeJohnsonand
Soenen(2003),Mobareketal. (2016). TheseresearchersalsoreportthatthehighertheGDPgrowth
ratedifferencebetweenthemarketpairs,thelowerwillbetheco-movementbetweenthetwostock
markets. Worldmarketvolatilityisthesecondimportantdeterminantofstockmarketco-movement
betweenPakistanandKorea. ThecoefficientestimatefortheworldmarketvolatilitybetweenPakistan
andKoreaissignificantandpositive. Suchresultsareconsistentwithpreviousresearchworklike
BrackerandKoch(1999).
Table8.DeterminantofStockMarketCo-movementbetweenPakistanandKorea.
Variable Coefficient Std.Error t-Statistic Prob
C −0.097 0.127 −0.763 0.449
Tradeijt 0.163 0.124 1.314 0.196
GDP −0.022 0.010 −2.091 0.043
IND 0.003 0.002 1.186 0.243
INF 1.90×10−5 0.005 0.003 0.997
INT 0.001 0.012 0.154 0.877
WLDVOL 0.005 0.002 2.177 0.035
XRCH −3.311 0.973 −3.401 0.001
XRSD −85.947 29.595 −2.904 0.006
R-squared 0.316
Prob(F-statistic) 0.056