Introduction
Theoilcrudepriceshasfallenlessthan$50perbarrel,about50%ofAugust2015.Them ainreasonistheoilsupplymorethandemand(seethefigure1).Growingoilinventoriesand supply typicallyputdownwardpressureonnear- termprices.The U n i t e d Statesdiscoveredandappliedthenewoildrilltechnology ,called“shaleoilrevolution”.This pushestheoilproductionisnear10millionbar relsperday.S o t h a t itcanbeoffsetthesubstantialoilsupplydisruptionintheOrga nizationoftheP e t r o l e u m E x p o r t i n g C o u n t r i e s ( O P E C ) H o w e v e r , t h e r e s u m p t i o n o f s i g n i f i c a n t Libyanoilproduction,combinedwiththeweakeningou tlookforglobaloildemand,t h e largeeconomiesinthewordsuchasChina,Russia,Europ eareashownotgoodperformancesaboutindustrialproductionandexpectationforeconomi cgrowth.
Figure1.1Globalcrudeoil andpetroleumliquidsconsumption,supplyandinventoryin2014 and2015(Source:EnergyInformationAdministration).
On July 14, the P5+1, which includes the five permanent members of the United Nations Security Council and Germany, reached an agreement with Iran that may lead to the easing of nuclear-related sanctions imposed by the United States and the European Union, including some oil-related sanctions If this agreement is implemented and sanctions relief occurs, it could increase Iranian oil supplies in a global market that has already experienced a significant rise in oil inventories over the past year, contributing to downward pressure on oil prices.
Vietnami s n e t e x p o r t e r o f c r u d e o i l , b u t i s a n e t importero f o i l p r o d u c t s , t h e volatilitiesi n c r u d e o i l p r i c e s o r c o s t s o f r a w materialss h o u l d a f f e c t t o r e v e n u e r e s o u r c e ofstatebudgetandeconomicgrowth.Volatilitiesofworldcrud eoilpricec a n a f f e c t n e g a t i v e l y o r p o s i t i v e l y t o p r o f i t o u t l o o k s o f t h e l i s t e d c o m p a n i e s o n Vietnams t o c k m a r k e t T h e c o m p a n i e s h a v e i n p u t s f r o m t h e o i l w a s t e p r o d u c t s ( su ch a s P L V -
P e t r o V i e t n a m G a s C o r p o r a t i o n ) a r e l i k e l y tob e impactedn eg at i v e bythedecreaseofoilprice.
Thefigure 1.2 showsthatrevenuesandproductionsfrom2009-2015.The crudeoilp r i c e s h a v e d e c r e a s e d s i n c e t h i r d q u a r t e r i n 2 0 1 4 , s t r o n g l y a f f e c t i n g t o c r u d e o i l r ev en u es in2015althoughtheexportproductionsis bigg erthanthesameperiod.Wearetheoneofemergingcountryanditseconomydepend sverylargeinexportactivities.Thedeclineofcrudeoilpricewillimpacttobudgetrevenuesa nddeficit
Energy,inparticularcrude oilhasplayedanimportantrole inoureconomy Th ep u r p o s e ofthisstudyistoinvestigatetherelationshipbetweencrudeoilpricea ndVietnams t o c k market.I n t h i s p a p e r , I w i l l a n s w e r t h i s q u e s t i o n f r o m s e v e r a l p e r s p e c t i v e s :
(ii) Dothebigworldeventssuchasthefinancialcrisisin2007andthetechnologyshock called“shaleoilrevolution”affecttotheco-movementofthethree?
F2a.Crudeoilexportvalue( u n it : 1billiondollars) F2b.Crudeoilexportproduction( u n i t : $1billionton)
Figure1.2Crudeoilexportrevenuesandproductionsfrom2009to08monthsof2015(source: GeneralStatistics OfficeofVietnam).
Thestudywillprovideinvestorsthemarketoutlookinthefuturebeforetheoilpricef l u c t ua t i o n s inthepresent.Therefromtheinvestorcanmaketheappropriateh e d g in g s t r a t e g i e s a n d d i v e r s i f i c a t i o n S p e c i a l l y , f o r a c o u n t r y w h i c h t h e f o r e i g n currency primarilycomesfromexportingnaturalresourcessuchascoals,oil… likeu s , thenthestrongoilpricevolatilitieswillsnappilyimpactitsinternationalb a la n c e s, budgetdeficitsandeconomicgrowthrates.Throughthisstudy,Ihopetop r o v i d e furtherevidencesabouttheenergyimportancetotheeconomyandsuggestsoluti onsthatgovernmentcanintercepttoreducemarkervolatilities
2 0 1 5 Year2006chosenisthebeginningstudyyear,becauseVietnamstockmarket hasjusthadstepsonobviousdevelopmentinnumbersoflistedcompaniesan dtra dingvolume, andcanreflectpartlyeconomicsituation The entiresamplesisd i v i d e d into04phases,thefirstphasefrom01/03/2006to12/28/20 07,thesecondp h a s e f r o m 0 1 / 0 2 / 2 0 0 8 t o 1 2 / 3 1 / 2 0 0 9 , t h e t h i r d p h a s e f r o m 0 1 / 0 4 / 2 0 1 0 t o 0 6/ 30/2 014andthe lastphasefrom 07/01/2014 to08/31/2 015,attaching withthesignificantdeclineinoilpricessincethebeginningofJuly2014du etoexcessiveoils u p p l y whiletheworldeconomyisstillgloomyandhasnotyetrecovered.
The results indicate a long-run nexus between the variables examined, yet the null hypothesis of no cointegration cannot be rejected at a significant 5% level across all four phases This suggests that events occurring during the research stage affect the long-term structure of oil prices and the stock market The interruptions prevent achieving equilibrium within the limited timeframe of the subsample.
Yamamoto (1995) demonstrates a unidirectional relationship where oil prices influence stock prices across the entire sample, particularly in the second and third phases following the 2007 financial crisis Contrary to expectations, crude oil prices do not significantly Granger-cause stock prices in the last phase, suggesting that the effects of oil prices on the stock market may require several lags to manifest, and the duration of this phase is insufficient to observe them Additionally, while some industries benefit from declining oil prices, others suffer damages, indicating a complex balance between advantages and disadvantages during this period.
ErrorC o r r e c t i o n M o d e l indicatest h a t o i l p r i c e s a n d s t o c k p r i c e s h a v e a p o s i t i v e r el a t i o n s h i p in shortterm.The reasonmaycomefromtheoilindustry’sstocks have largemarketcapitalizationandsignificantimpacttothemarketindex.Thedeclineo f oilpriceswillleadthesestocksofthesecompaniesplummet,marketsentimentint h e shortt ermpushthemarketindexdecrease.However,theexchangeratesdon’ta f f e c t th estockmarketintheshortterm.Thespeedofadjustmentofstockpricetoreturntheequ ilibriumstateafterashockisslowaround0.25%.
Thestudyalsosuggestsomepoliciesthathelpthegovernmentinterceptthemarketto red uce thenegativeeffectfromtheenergyshocksingeneralandoil priceshocksi n particular.Thosearetopayingmoreattentiontodomesticproductio nandtrader e v e n u e s t o g e t mores t a b l e b u d g e t , r e s e a r c h t h e a l t e r n a t i v e e n e r g y a n d e n h a n c e internationalcooperationintheenergysector.
Theoutlineofthisstudyisstructuredasfollow:Section1introduction;sectio n2literaturereviews and overallaboutVietnamstockmarket,oilsector,andExchangeregime;section3dataandresea rchmethod;section4researchingresulta n d section5 conclusion.
LiteratureReview
LiteratureReview
Chen (2010) explores the relationship between high oil prices and the potential for a bear market or recession in the stock market Utilizing monthly data from 1957 to May 2009, he analyzes returns on the S&P 500 as a proxy for stock market performance, measuring oil price shocks through various methods, including changes in oil prices and scaled oil price increases The study employs a time-varying transition-probability Markov-switching model to assess the likelihood of transitions between bull and bear markets, revealing that rising oil prices significantly increase the probability of a bear market occurring.
Juncala n d F e r n a n d o ( 2 0 1 3 ) e x a m i n et h e impacto f o i l p r i c e s h o c k s o n s t o c k r e t u r n s in12oilimportingEuropeaneconomiesusingVectorAutoregress ive( V A R ) a n d V e c t o r E r r o r C o r r e c t i o n M o d e l s ( V E C M ) f o r t h e p e r i o d 1 9 7 3 M 2 –
20 11 M12 Theoilpriceshockswasdividedinto02kinds,theyareoilsupplyand oild e m a n d s h o c k s , w h i c h a r e measuredbyw o r l d o i l p r o d u c t i o n a n d w o r l d o i l p r i c e s respectively.Moreover,thereareotherexplanationvariablesaddedtomod elss u c h asindustrialproductionindexes,short- terminterestratesinordertoexpress differentc h a n n e l s t h r o u g h w h i c h o i l p r i c e s c o u l d a f f e c t s t o c k r e t u r n s
T h e mainco n t r ib u t io n i s i d e n t i f i c a t i o n t h a t s t o c k r e t u r n s mayr e s p o n d in d i f f e r e n t wayst o supplyanddemandshocks.Theoilsupplyshockstendtohave agreaternegativei m p a c t ons t o c k m a r k e t r e t u r n s t h a n o i l d e m a n d s h o c k s Generally,t h e o i l p r i c e ch a ng e lowerseconomicactivityi n oilimportingeconomi esbecauseofmoree x p e n s i v e energyinputs.However,iftheincreasecomesfromde mandshock,theneconomica c t i v i t y i n o i l i m p o r t i n g e c o n o m i e s c a n b e i m p a c t e d n e g a t i v e ( d u e toh i g h e r p r o d u c t i o n c o s t ) o r p o s i t i v e (duet o i n c r e a s e w o r l d incomea n d consumption).
This article highlights the significant impact of oil price changes and volatility on the Korean stock market, particularly as Korea is a net oil-importing country Utilizing a Vector Error Correction Model (VECM) with monthly data from May 1988 to January 2005, the study examines the relationships between interest rates, industrial production, real stock returns, real oil prices, and oil price volatility The findings reveal a long-run and stable relationship among these variables, indicating that oil price movements notably affect stock returns, with real stock returns serving as the primary channel for short-run adjustments to long-run equilibrium The study identifies two main pathways through which oil price changes influence firm profitability: production costs and investor sentiment towards stock market indices Additionally, the authors propose three strategies to address high and volatile oil prices, including increasing government strategic oil reserves, implementing oil-saving measures, and enhancing dialogue with oil-exporting countries.
(2014)examinestheimpactofstructuraloilpriceshocksonthec o v a r i a n c e oft heUSstockmarketreturnandstockmarketvolatilitybyusingtheSVARm o d e l i n p e r i o d f r o m J a n u a r y 1 9 7 3 t o D e c e m b e r 2 0 1 3 T h e S V A R w i t h r e c u r s i v e structuralrestrictionsfollowsuptheorderofvariablessuch as:oilsupply,aggregate demand,oilmarket- specificdemand,andcovarianceofreturnandvolatility.Positiveshockstoaggreg atedemandandtooil-marketspecificdemand areassociatedwithnegativeeffectsonthecovarianceofreturnandvolatility Anunanticipated r e d u c t i o n i n c r u d e o i l p r o d u c t i o n i s a s s o c i a t e d w i t h a s t a t i s t i c a l l y significantincreaseimplied- covarianceofreturnandvolatility.Thespilloverindexbetween thestructuraloilpric eshocksandcovarianceofstockreturnandvolatilityislargeandhighlystatisticallysignif icant.
Pacificstockmarketreturns.Therearemanydifferentapproaches, however,tr aditionalapproachessuchasVARorVECMrequirevariablesfollownormalo rStudentt-distributions.Furthermore,itis wellknownthattraditionalmeanvarianceoptimization analysisp o r t f o l i o s a re s y m m e t r i c measurest h a t can no t c a p t u r e non- l i n e a r dependenceorchangesinthetailsofassetreturncurvesandthatinve storspayc l o s e r a t t e n t i o n t o d o w n s i d e t h a n t o u p s i d e r i s k T h e modelp r o p o s e d i s t h e copula-
P a c i f i c countries'stockreturnsfromJanuary4,2000toMarch30,2012.Thedataisdivide dintotwosubsamplesreferredtoaspre- crisis(January4,2000to23September2 0 0 8 ) a n d p o s t - c r i s i s ( S e p t e m b e r 2 4 , 2 0 0 8 toM a r c h 3 0 , 2 0 1 2 ) , r e s p e c t i v e l y toexplored ifferencesofthedependencebetweenphases.Theresultssh owthatthedepen dencebetweencrudeoilprices andAsia-
Pacificstockmarketreturnsisg e n e r a l l y w e a k , t h a t i t w a s p o s i t i v e b e f o r e t h e g l o b a l f i n a n c i a l c r i s i s , excepti n H o n g K o n g , a n d t h a t i t i n c r e a s e d s i g n i f i c a n t l y i n t h e a f t e r m a t h o f t h e crisis.Theyfoundthatthetaildepe ndencewasveryweakbeforethecrisisandthatthelowertaildependencewasmuchhigh erthantheuppertaildependenceafterthec r i si s , exceptinthecasesofJapanandSingapore.
A study conducted in 2013 analyzed the sensitivity of Spanish industries to oil prices from January 1993 to December 2010, utilizing weekly observations of stock market returns, industry performance, Brent crude oil prices, and interest rates Employing a multifactor market model, the research assessed the impact of oil price fluctuations on industry stock returns, with a focus on sub-samples identified through structural break tests The findings revealed that Spanish industries have limited exposure to oil price changes, though this exposure varies significantly across different sectors In the 1990s, during a period of stable and low oil prices, the exposure was minimal, but it increased in the 2000s amid rising and more volatile oil prices The study also noted that aggregate demand-side oil price shocks are influenced by fluctuations in the global business cycle, resulting in a correlation between crude oil prices and the Spanish equity market.
This study examines the relationship between oil prices and stock markets, specifically in the Gulf Cooperation Council (GCC) nations, by assessing whether oil price risk is systematically priced in stock returns Utilizing firm-level data from Gulf Arab stock markets between March 31, 2004, and March 31, 2013, the research incorporates stock prices, shares outstanding, book equity, exchange rates, the three-month U.S Treasury Bill rate, and Brent crude oil prices The findings reveal that stocks more sensitive to oil price fluctuations yield significantly higher returns, indicating that oil price risk exposure can act as a return predictor in these markets However, there is no substantial evidence of a risk premium linked to oil price risk when accounting for firm-level risk factors, suggesting that variables such as firm size and idiosyncratic volatility mitigate the significance of oil price risk in stock returns.
0 1 t o D e c e m b e r 2 0 1 0 i n c l u d i n g m o n t h l y r e a l o i l p r i c e , t h e r e a l s t o c k p r i c e indicesfort h e 13majorsectorsa n d a c o n t r o l l i n g v a r i a b l e , i n t e r e s t r a t e T h e i r findingsshowthatthereexista positive relationship betweenoilpricesandsectoralstockpricesinthelongrun.Itmayalsoindicatethatthei mpactofothersubstituteenergysources(e.g.,coal)orotherinternalanddomesti cfactorsonthesesectorals to c k s a r e mored o m i n a n t t h a n t h e i n c r e a s e i n oil p r i c e s T h e r e s u l t s o f G r a n g e c au s a li t y t e s t s f i n d a u n i d i r e c t i o n a l , l o n g - r u n a n d s h o r t - r u n r e l a t i o n s h i p r u n n i n g f r o m o i l p r i c e s a n d s e c t o r a l s t o c k s t o t h e i n t e r e s t r a t e f o r t h e p e r i o d 2 0 0 1 / 0 7 –
2007/06,t h e r e i s o n l y the unidirectionallong– runGrangercausalityrunningfromsectoralstockstooilpricesa n d f r o m s e c t o r a l s t o c k s t o t h e i n t e r e s t r a t e Additional,t h e l o n g - r u n G r a n g e r causalit y isbidirectionalbetweenoilprices,theinterestrateandse ctoralstocksfor2007/08–2008/11and2009/01–2010/12.
ApergisandMiller(2008)modelstheimpact ofoilmarketshockstostockmarketreturns.T h e c o m p o n e n ts o f o i l m a r k e t s h o c k d e te r m i n e d bymodifyingt h e p r o c e d u r e o f K i l i a n ( 2 0 0 8 a ) i n c l u d e o i l - s u p p l y s h o c k s , g l o b a l a g g r e g a t e - d e m a n d shocks,andglobalo i l - d e m a n d s h o c k s T h e a u t h o r s u s e t h e m o n t h l y d a t a f o r t h e e ig h t countries -
A study analyzing stock market returns from 1981 to 2007 across Australia, Canada, France, Germany, Italy, Japan, the United Kingdom, and the United States reveals that different oil-market structural shocks significantly influence stock market adjustments, albeit with a small magnitude In Australia, oil-supply and global aggregate demand shocks do not significantly impact stock returns, while in Canada, idiosyncratic demand shocks affect stock returns at a weaker significance level Additionally, Granger temporal causality tests indicate that idiosyncratic demand shocks play a strong role in leading stock market returns, whereas oil-supply and global aggregate demand shocks typically do not temporally lead stock market returns.
Qatar,Oman,SaudiArabia,andtheUnitedArabEmirates.Thedatasetusedinthiss t u d y c o n s i s t o f d a i l y o b s e r v a t i o n s o f t h e S t a n d a r d & P o o r ' s ( S & P )
E m e r g i n g M a r k e t IndexesforsixcountriesfortheperiodApril03,2006thr oughMarch28,2 00 8a n d t w o b e n c h m a r k i n d e x e s f o r o i l a n d g o l d S i n c e t h e d a t a i s non-normalwitht i m e - v a r y i n g v o l a t i l i t y , t h e a u t h o r s a p p l y a n e w m e t h o d o l o g y b a s e d o n t h e leveragebootstrappedsimulationtechnique.T h e c a u s a l i t y t e s t r e s u l t s r e v e a l t h a t n e i t h e r theoilpriceindexnorthegoldpriceindexcausestheequitypriceindexesofthe sixGCCmarkets.Thismeansthattheinformationcontainedinthegoldandoilpriceinde xescannotimprovetheforecastoftheequitymarketindexineachofthesixGCCstates. Thus,thepossibilityofshort- termarbitrageisruledoutandthesixGCCequitymarketscanbeconsideredasinfor mationallyefficientwithrespecttooilandgoldprices.
2.1.1.4 Thei m p e r i a l e v i d e n c e s ab ou t t h e r e l a t i o n s h i p b e t w ee n o i l pr ic esa nd V i e tn a m stockmarket
VoX u a n V i n h ( 2 0 1 4 ) investigatesthelongandshort- runr e l a t i o n s h i p b e t w e e n Vietnam’sstockprices(VN-
Index)andtheUSstockprices(S&P500Index),theU S Dollar-
VNDongexchangerates,goldprices,andcrudeoilprices.Thepaperu se s th e d a i l y dat a f r o m 01 /0 4/ 20 05 t o 1 2 / 3 1 / 2 0 1 2 and d i v i d e s t h e en t i r e samplei n t o t wosub- periodstoaccounttheeffectof2008Globalfinancialcrisis,thefirsto n e i s 2 0 0
Indexandthecrudeoilprice.T h e evidencesfromthebivariatecointegrationtest showthatthereexistthelong- runrelationshipbetweenVNindexandcrudeoilpricesinthe wholeperiodsandtheseconds u b - p e r i o d Int h i s s u b p e r i o d , t h e r e o n l y e x i s t t h e l o n g r u n - r e l a t i o n s h i p b et weenVNindexandexchangerate.TheresultsofGrangeca usalitytestsfindaun id irect io nal relationshiprunningfromoilpricestothestock marketintheentirepe r i od a n d t h e f i r s t s u b - p e r i o d A d d i t i o n a l , t h e r e i s a u n i d i r e c t i o n a l r e l a t i o n s h i p r u n n i n g fromExchangeratetothestockpricesinthefirstsub-period.
The study examines the long-run relationships among stock prices, oil prices, and exchange rates using cointegration tests, including the Johansen test and structural break tests The findings indicate a significant positive effect of oil prices and exchange rates on stock prices, although these results contradict theoretical expectations The authors suggest that other factors, such as increasing foreign portfolio investment and local market participation, may have contributed to the stock market boom during this period Additionally, the research integrates a long-run model with a short-run model through an error correction model, revealing that while the determinants of stock prices are statistically significant in the long run, they appear insignificant in the short run.
Nguyen and Ishaq (2012) investigate the dependence structures
Exchange rates, represented by E and expected future exchange rates, influence the asset markets, particularly when domestic output declines, leading to a depreciation of the currency According to Aggarwal (1981), changes in exchange rates can directly affect the stock prices of multinational firms and indirectly impact domestic firms For multinational companies, fluctuations in exchange rates alter the value of their foreign operations, which is reflected in their balance sheets as profits or losses, contributing to current account imbalances Consequently, when a profit or loss is reported, the firm's stock price is likely to change The effect of devaluation on a firm's stock price can vary; it may increase for exporting firms or decrease for those reliant on imported inputs Firms engaged in both activities may experience stock price movements in either direction Overall, changes in exchange rates are anticipated to lead to stock price fluctuations, aligning with the traditional approach to understanding these economic dynamics.
As capital markets become increasingly integrated, changes in stock prices and exchange rates may reflect capital movements more than current account balances A portfolio approach suggests that a decrease in stock prices reduces domestic investors' wealth, leading to lower money demand and consequently lower interest rates These lower interest rates encourage capital outflows, which can result in currency depreciation Under this approach, stock prices are expected to negatively correlate with exchange rates If a market is influenced by both approaches simultaneously, a feedback loop may emerge, resulting in an arbitrary correlation between the two variables.
(1997)arethepioneersofusingcointegrationandGrangercausalitytechniquestoinvestigate theinteractionbetweenstockpricesandFXmarkets.Thed a t a t h e y u s e d c o n s i s t o f m o n t h l y S & P 5 0 0 ande f f e c t i v e e x c h a n g e r a t e s o f USdollarfromDece mber1973toDecember1983.Atwo- stagesystematica u t o r e g r e s s i v e p r o c e d u r e w a s employedd e v e l o p e d byH s i a o ( 1 9 8 1 ) T h e y f o u n d bidirectional causalityintheshortrun.However,ther eisnolong-runrelationshipb e t w e e n thevariables
Ajayi and Mougoue (1996) demonstrated a negative short-run and a positive long-run impact of stock prices on domestic currency value Their study utilized recent advances in time-series analysis to explore the intertemporal relationship between stock indices and exchange rates across eight advanced economies By employing an error correction model (ECM), they simultaneously estimated the short-run and long-run dynamics of these variables The findings indicated significant feedback relations between the two financial markets, revealing that an increase in aggregate domestic stock prices negatively affects domestic currency value in the short run Conversely, in the long run, rising stock prices positively influence domestic currency value Additionally, currency depreciation was found to have negative effects on the stock market in both the short and long run.
Roll( 1 9 9 2 ) a l s os t u d i e d t h e U S s t o c k p r i c e s a n d e x c h a n g e r a t e s a n d f o u n d a p osit iv e r e l a t i o n s h i p b e t w e e n t h e t w o m a r k e t s Ont h e o t h e r h a n d , C h o w e t a l
AbdallaandMurinde(1997)studiedthepricesinFXandstockmarketsinfourle s sdevelopedcountries,namely India,Korea,Pakistan,and Philippines wit hinaV E CM (vectorerrorcorrectionmodel)framework.FortheperiodJanuary19 85toJ u l y 1994, theyfind unidirectionalcausallinkagebetween exchangeratesandstockp r i c e s forPakistanandKorea.Therealeffectiveexchan gerateGrangercausethestockp r i c e i n d e x i n I n d i a , b u t n o c a u s a l r e l a t i o n s h i p w a s f o u n d i n t h e c a s e o f Philippines
A study conducted in 1998 analyzed the relationship between daily stock returns and changes in exchange rates across two market groups: advanced economies (including Canada, Germany, France, Italy, Japan, the UK, and the USA) from April 1985 to August 1991, and Asian emerging markets (including Taiwan, Korea, the Philippines, Malaysia, Singapore, Hong Kong, Indonesia, and Thailand) from December 1987 to September 1991 The findings revealed a one-way causal relationship from the stock market to the foreign exchange market for Indonesia, the Philippines, Taiwan, and all advanced markets, while Korea exhibited the opposite relationship Causality tests on weekly data corroborated the daily data results for advanced markets However, a distinct outcome emerged for emerging markets, indicating a unidirectional causal relationship from stock returns to exchange rate changes specifically in Thailand and Malaysia.
This study applies the Granger causality test and impulse response function (IRF) to explore the interaction between stock prices and foreign exchange (FX) markets in nine Asian countries: Hong Kong, Indonesia, Japan, South Korea, Malaysia, the Philippines, Singapore, Thailand, and Taiwan, using daily data from January 3, 1986, to November 14, 1997 The analysis is divided into three sub-periods: the initial period until November 30, 1986; the post-crash period from December 1, 1987, to the end of 1994; and the remaining observations In the first period, significant causal links are found only in Hong Kong and South Korea The second period reveals a one-way causation from FX markets to stock markets in Malaysia and the Philippines, while a reverse causation is noted in Taiwan In the final period, stock price changes lead to changes in exchange rates in Taiwan, with reverse relationships observed in Japan, Thailand, Singapore, and Hong Kong Bidirectional causal relationships are established in the remaining markets, indicating that incorporating exchange rate variations can enhance the predictability of stock price changes.
OverviewaboutVietnamstockmarket,oilsectorandexchangerateregime
Vietnami s a M S C I f r o n t i e r marketl i k e s P a k i s t a n , S r i L a n k a a n d B a n g l a d e s h F r o n t i e r marketsareinvestable buthavelowermarketcapitaliza tionandliquiditythanthemoredevelopedemergingmarkets.
Vietnam hastwostockexchanges– theHoChiMinhStockExchange(HOSE)andt h e HanoiStockExchange(HNX). HOSEismostlydedicatedtoequitiestrading,whileHNXtradesequities,bondsan doverthecountersecurities.
HOSEwasinitiallyestablishedastheHoChiMinhCitySecuritiesTradingCenter(H oS T C) in2000.Itwas laterupgradedan drenamedin2007.PriortoMarch1 st2 0 0
2 ,shareswereonlytradedonalternatedays.TheVietnamequitiesmarkethascom ealongwayinashorttime.InJanuary2006,therewereonly34companiesl i s t e d onHOSE;thishasincreasedto303in2012,withthemarketcapexpandingfrom USD1.1billionin2006toUSD29.9billionin2012.In2015,thereare600-
Figure2.1showsthemarketcapitalizationtoGDPfrom2004to2016.Thisratio significantlyincreaseso v e r year-to-year.I n 2 0 1 3 -
2 0 1 4 , t h e m a r k e t c a p i t a l i z a t i o n a c c o u n t e d about31%GDPandincrease d24%comparedto2006.However,comparedwithotheremergingmarketssuchasChin a,India,andSouthAfrica,thenV i e t n a m stockmarketisrelativelylessdeveloped.
Banking-insurance 19%Food 32%Real estate 4%Contruction 6%Electricity/ gas Energy 6%Oil industry 7%14%Transportantion 12%Others
Figure2 2 e x p r e s s e r t h e p r o p o r t i o n o f s e c t o r a l marketc a p i t a l i z a t i o n i n 2 0 1 5 Its h o w s thatoilindustryhasthefifthpercentageofmarketcapitalizati onabout6%.Therefore,thevolatilitiesinworldoilpricesmayhaveanimmediateim pactonthemarket.
OverthepastfewdecadesVietnamhas emergedasanimportantoiland naturalgasproducerinSoutheastAsia.Vietnamhasboostedexplorationactivities,allo wedforgr eat er foreigncompanyinvestmentandcooperationintheoilandgassectors ,andintroducedmarketreformstosupportthee n e r g y industry.Thesemeasureshaveh e l p e d t o i n c r e a s e o i l a n d g a s p r o d u c t i o n A l s o , t h e c o u n t r y ’ s r a p i d e c o n o m i c growth,industrialization,andexportmarketexpansionhaves purreddomesticenergy consumption.
Recent,successfuloffshoreexplorationhascontributedtoasubstantialincreasei nprov ed crudeoilreserves,whichgrewto4.4billionbarrelsasofJanuary2012from
0.6billionbarrelsin2011,accordingtotheOilandGasJournal.Reservesremaineda t 4.4bill ionbarrelsin2013and2014.Ongoingexplorationactivitiescould increasethisfigureinthefuture,asVietnam’swatersremainlargelyunderexplored.V i e t n a m iscurrentlythethird- largestholderofcrudeoilreservesinAsia,behindC h i n a andIndia.
Vietnam,thePhilippines,Malaysia,C h i n a , Taiwan,a n d Bruneieachc l a i m sovereignt yoverthe SpratlyIslandsintheSouth ChinaSea However,Vietnam hasr e a c h e d agreements withseveral ofitsneighborsto conductjointexploration foroila n d naturalgasresourcesintheregion.DisputeswithChinaareyettoberesolved.
2014,tensionsbetweenChinaandVietnamflaredfollowinga skirmishoveraChineseoilri gthatVietnamclaimswasplanningtoillegallydrilli n t o theVietnam'scontinentalsh elf.Inaddition,onSeptember15,2014,Vietnama n d I n d i a a g r e e d t o e x p a n d j o i n t u p s t r e a m o i l a n d g a s a c t i v i t i e s int h e c o n t e s t e d wat er s oftheSouthChina Sea,despiteChina'sobjections.
AccordingtoMinistryofIndustry andTrade,inSeptember20 15, t h e nationwi dec r u d e oilproductionisestimatedatabout13.9milliontons,increase9%compared w i t h thesameperiodof2014.
Bytheway,gasproductionisestimatedat7.8billionm3,increase1.8%comparedw i t h thesameperiodof2014.Petroleumproductionisestimated5.1milliontons,incre ase25.7%comparedwiththesameperiodof2014.
Vietnamproducedaround353,700barrelsperday(bbl/ d)ofoilin2013,whichisr ou gh ly 3%l e s s t h a n w h a t i t p r o d u c e d in2 0 1 2 a n d
Vietnamisanetexporterofcrudeoil,butisa netimporterofoilproducts.Withoilcon su mp tio n increasingyear-over- yearandoverallbymorethan70%from238,400b b l / d i n 2 0 0 4 t o 4 1 3 , 0 0 0 b b l / d i n 2 0 1 3 , t h e c o u n t r y musti m p o r t a m a j o r i t y o f r e f i n e d productstosatisfy demand.
Vietnam operates one refinery, the Dung Quat refinery, which has a capacity of 140,000 barrels per day and began operations in 2009 The state-owned Vietnam Oil & Gas Corporation (PetroVietnam) aims to increase crude distillation capacity to approximately 200,000 barrels per day by 2017 and enhance Dung Quat's capability to process sweet and less expensive crude oil from Russia, the Middle East, and Venezuela To finance the upgrade and expansion of Dung Quat, Vietnam plans to offer 49% of the refinery's equity to foreign investors Additionally, the Nghi Son refinery is currently under construction and is expected to commence operations in mid-2023.
2017andtheVungRorefinery,w h i c h w i l l bed e s i g n e d byJ a p a n ' s J G C C o r p o r a t i o n , i s e x p e c t e d tob e completedin2019.
PetroVietnamisthekeycompanyintheoilandnaturalgassectorsandservesasthep r i m a r y o p e r a t o r a n d r e g u l a t o r o f t h e i n d u s t r y O i l a n d n a t u r a l g a s p r o d u c t i o n i s e it her undertakenbyPetroVietnam'supstreamsubsidiary,PetroVietnamE xploratio nandProduction(PVEP),orthroughPetroVietnam'sjointventure withother companies.
InternationalOilCompanies (IOCs)suchasExxonMobil,Chevron,andZarub ezhnefthave formed partnershipswithPetroVietnam.IOCsmustr e c e i v e approvalfromtheOilandGasDe partmentofthePrimeMinisterandmustnegotiateup st r e a m licenseswithPVEP.
Averageo i l p r i c e i n September2 0 1 5 i s a b o u t 4 8 U S D / b a r r e l , t o t a l e x p l o i t i n g p r o d u c t i o n o f P V N byt h e e n d o f S e p t e m b e r i s estimatedata b o u t 2 1 8 6 milliontons.Inthisperiod,thegroupexports11.9millionton sofcrudeoilbuttherevenueo n l y reaches3.05billiondollarscomparedtoSeptember2014 exporting6.8milliont o n s , r e a c h i n g 5 9 8 b i l l i o n d o l l a r s T h e c r u d e o i l p r i c e h a s d e c r e a s e d l e a d i n g t h e exportingvolumeincreasesbuttheexportingrevenuestillde crease.
In 2013, Vietnam produced 346 billion cubic feet of marketed natural gas, all of which was consumed domestically, according to the BP Statistical Review of World Energy 2014 While the country is currently self-sufficient in natural gas, PetroVietnam forecasts a growing supply gap as demand exceeds supply, particularly in southern Vietnam The 2011 Gas Master Plan outlines initiatives to enhance the role of natural gas in the primary energy mix, sets targets for gas production and consumption, and includes detailed infrastructure plans for gas gathering systems, pipelines, and gas processing facilities.
TheVietnamesegovernmenthasconsideredimportingliquefiednaturalgas(LNG)in thesouthernpartofthecountrytomeetgrowingnaturalgasdemandandfillthesupply gap.PetroVietnamGas,asubsidiary ofPetroVietnam,signed am e m o r a n d u m ofunderstandingandafront- endengineeringanddevelopmentc o n t r a c t withtheTokyoGasCompanytodevel optheThiVaiLNGterminalintheV u n g T au p r o v i n ce T h e t e r m i n a l is e x p e c t e d t o b e o p e r a t i o n a l i n 2 0 1 7 P V G a s alsosignedagassalesandpurchaseagreemen twithGazpromofRussiaonMarch6 , 2014.Undertheagreement,PVGaswillrecei ve48Bcf/ yviatheThiVaiLNGterminal.Asecondterminal,SonMyLNG,isalsoplannedforoperatio nsstartingin2 0 1 8 , althoughconstructionhasyettobegin.
InVietnam,exchangeratepolicycanbeseenasapartofmonetarypolicytoaffectto s u p p l y a n d d e m a n d o f f o r e i g n c u r r e n c y o n e x c h a n g e m a r k e t a n d a r c h i v e t h e targetsofmonetarypolicyistocontrolinflationandstabilizethepurchasingpowero f money,encourageexports,restrictimportsandenhancetheeconomicgrowth.
Vietnamofficiallyappliesthepeggedexchange rateswithcrawling bandsinMarch1 9 8 9 Accordingtothisexchangeregime,theexchangeratesofcom mercialbanks
1 9 9 1, c o m m e r c i a l b a n k s w e r e f o l l o w e d t o d e t e r m i n e e x c h a n g e rat es note xceeding0.5%ofofficialexchangerates.
After Vietnam joined the World Trade Organization in 2007, foreign investment capital flows surged, leading to an excess supply of foreign currency and causing commercial bank exchange rates to remain at the lower end of the allowed range However, the financial crisis in the latter half of 2008 reversed this trend, resulting in increased inflation, a growing trade deficit, and a significant gap between domestic and foreign oil prices, which pushed exchange rates to the upper bound of the allowed range in 2009 In response, the State Bank of Vietnam (SBV) had to continually raise the official exchange rate and ease trade restrictions Notably, on November 26, 2009, the SBV officially adjusted the basic exchange rate by 5.4%, marking the highest daily increase in a decade.
USDsi n ce theendofJune,2013.Thetradebandwasfixedat1%sincethebeginningof
However,ChinastronglydevaluatestheirRenminbicurrencyandthemarketinvest orsarebeingworryabouttheUSFederalReserveSystem(Fed)isgoingtoad ju s t interestrates.Inordertoactivelyleadthemarketanddealwiththeadverseimpact sofpossibilityofincreaseofinterest ratefromFed,SBVadjuststhe averageinterbankexchangeratefrom21,673VND/USDto21,890VND/USDappliedfrom
NHNNdecisiona b o u t VNDspotratesofcommercialbanks,accordingtoit,thebandofV ND/USD isadjustedfrom±2%to±3%.
Dataandresearchmethodology
Data
DailydatasetconsistingofBrentcrudeoilprice,averageinterbankexchange rateand Vietnam stock m a r k e t indexproxiedbyVNindex i s ch ose ni npe ri o ds f r o m 0 1 / 0 3 / 2 0 0 6 t o 0 8 / 3 1 / 2 0 1 5 AlthoughV i e t n a m s t o c k m a r k e t o f f i c i a l l y s t a r t e d i n 2 0 0 0 , d u r i n g 2 0 0 0 -
2 0 0 5 t h e markets i z e onlyr e a c h e d 1 % G D P a n d t h e m a r k e t activitieswasfa irlyquiet.From2006,thestockmarkethadsignificantly chancesa b o u t bot hnumberoflistedcompaniesandtradevolume.Specifically,themarkets i z e hada hugeleapto22.7%GDPandmoreover,capitalmobilizationsuchIPO,issuingbo nd,indeedonlyincurredfrom2006onward.Thereforethebeginningyearo f studyperiodis 2006toensurethestockmarketbeabletoreflecttheeconomicsituation.
Manyimportanteventshasincurredduringthestudyperiodsuchas2007financialcri si s, USAshaleoilrevolutionhaveenormousimpactsoneconomy,stockmarket,o i l p r i c e s , T o h a v e a b e t t e r i n s i g h t , w e d i v i d e t h e s t u d y p e r i o d into0 4 p h a s e s attachedt o 0 2 m a i n e v e n t s , t h o s e a r e 2 0 0 7 f i n a n c i a l c r i s i s a n d U S A s h a l e o i l r evolutionin2014(Seethefigure3.5).
Thefirstphasefrom01/03/2006to12/28/2007iscalledpre- crisisphase(seefigure3.1):i n t h i s p h a s e , t h e V i e t n a m s t o c k m a r k e t w a s t h e m o s t f l o u r i s h a n d v i b r a n t Intheendof2006,VN- indexincreasedby2.5comparedtointhebeginningofyear,ledt o t h e marketcapitalization reachingUSD
13.8b i l l i o n accountedabout22.7%GDP.Thenumberofthelistedcompanies wasupabout5times,VN- indexrisefurther500pointsfrom300pointsinthelate2005to800inthela te 2 0 0 6
S ec u r i t i e s l aw i n e f f e c t f r o m J a n ua r y 01 st ,2 01 5 h a s c o n t r i b u t e d i n promotin gthedevelopmentandintegrationofthestockmarket.Thetransparencyoft h e listedcompan ieshasbeenstrengthened.A ft er thatVN- indexpeakedat1,170.67andincreasedby23.3%comparedtothelate2006.Itcanbes aidthatthe marketreachedthebiggestgrowthrateinthisstage,especially;thisrateis126
%j u s t withinthefirstquarter InHCM Exchange, the averageof trade volu mewas morethanVND1,000billion/sessionanditwasVND300millionatHNX.
Thesecondphasefrom01/02/2008to12/31/2009(seethefigure3.2)iscalledcrisisphas e:Alongt o t h e g e n e r a l t r e n d o f e c o n o m y , V i e t n a m s t o c k marketi n 2 0
0 8 sharplydeclined I t wa s i m p ac t e d d i r e c t l y bym a c r o - ec o n o m i c i n s ta b i l i t y suchas t h e inflationincrease,largetradedeficitthatforced thegovernmenttomakeatightmo n et ar y policyandsqueezethecashflowsintosecuri ties.Additionally,the influenceofglobalfinancial crisishadtheVN-indexbottomed at235.5 pointsasof0 2 / 2 4 / 2 0 0 9
Thethirdphasefrom01/04/2010to06/30/2014iscalledaftercrisisphase(seethefi g ur e 3 3 ) : T h e s t o c k marketa l s o s n a p p i l y c h a n g e s b u t i t w a s f o l l o w i n g t o a positive trend in 2010-2012.Fromthebeginningof 2013,the marketshaped aquietcertain r e c o v e r y t r e n d A s o f t h e e n d o f 2 0 1 3 , V N - i n d e x r e a c h e d 5 0 5 p o i n t s , up2 3 % V i e t n a m s t o c k marketw a s c o n s i d e r e d a s o n e o f t h e 1 0 m a r k e t s w i t h t h e strongestrecovery growth anddegreecomparedtotheworld.Thisistheperiodthatthecrudeoilpriceremainedatthesta blelevelsmorethan$100/barrel.
Thelastphasefrom 07/01/2014t o08/31/2015(seethe fi rg ur e3 4 ) i s called
US A s h al e oilrevolutionphase:Crudeoilpricesfellsharplyinthefourth quarterof2014a s r o b u s t g l o b a l p r o d u c t i o n e x c e e d e d d e m a n d A f t e r r e a c h i n g m o n t h l y p e a k s o f
$112perbarreland$105perbarrelinJune,crudeoilbenchmarksBrentfelltolessthan$ 50/ barrelinAugust.Inadditional,ontheAugust,18th2 0 1 5 ,StatebankSBVad ju st s theave rageinterbankexchange rate f ro m 21,673VND/
USDto 21,890i no r d e r toactivelyleadthemarketanddealwiththeadverseimpactsof possibilityofincreaseofinterestr a t e f r o m Fed.T w o e v e n t s s i g n i f i c a n t l y i m p a c t t o V i e t n a m economy.
Stockprice Vietnamstockmarket Lvni Ho Chi Minh City stock index–VN-Index.It’s exchangewebsite transformedby https://www.hsx.vn/ logarithm
It’stransformedby InformationA d m i n i s t r a t i o logarithm n(EIA):www.eia.doe.gov
Exchange Inter-bankaverage Lex WebsiteoftheStateBank of rate exchangerate.It’s Vietnam(SBV): transformedby http://www.sbv.gov.vn/
Methodology
GHtestwasdevelopedbyGregoryandHansen(1996),thisisaresidual- basedtesto f cointegrationwithnullhypothesisisnocointegrationandalternativehy pothesist h a t theremaybeonebreakinthecointegratingvector.Thetestisanextens ionoftheADF,Zt,andZatestforcointegrationandis non- informativewithrespecttothet i mi n g ofthebreak.Totestbreakpointsincointegra tionvector,theauthorsusedthreealternativemodels:
(ii)levelshiftwithtrend(onlyslopecoefficientscanchange)and(iii)regimeshift(bot hintercepta n d slopecoefficientscanchange).
Inthisstudy,Iusethethirdmodel“regimeshift”.Thedependentvariableislvni a n d independentvariablesarelexandloil.Thestandardmodelofcointegrationwithatrendan dnostructuralchangeis:
𝑖 �> [ 𝜏� ] Wheretheunknownparameter𝜏∈(0, 1) denotesthe(relative) timing ofthec h a n g e point,and[ 𝜏� ]denotesintegerpart.Theregimeandtrendshiftalternative is:
Lvni t =α 0 +α 1 D 1t +β 01 Loil t +β 11 D 1t Loil t +β 02 Lex t +β 12 D 2t Lex t +ε t
Fuller),Zαa n dZt( p r o p o s e dbyPhillips,1987)isnotnol o n g e r consistenttotestthenull ofnocointegrationwhenthereisaregimeshiftasinequation(2)andproposedbias- correctedmodifiedADF*,Zα*andZt*test:
Where𝜏∈T.InprinciplethesetTcanbeanycompactsubsetof(0,1).Inp r ac t i c e, itw i l l b e t o b e s m a l l e n o u g h s o t h a t a l l o f t h e s t a t i s t i c s d i s c u s s e d h e r e c a n b e calculated.A s t a n da r d c h o i c e is T = ( 0 1 5 , 0 8 5 ) A l t h o u g h i t c o n t a i n s a n u n c o un t ab le numberofpoints,soit’simportanttoconsiderthestepfunctionsonTtakin gjumponlyonthepoints{(i/n),Integer}.Forthecomputationpurposes,the teststatisticiscomputedforeachbreakpointintheintervalT=([0.15n],
3.2.2 Toda-Yamamoto(TY)versionofGrangernon-causalitytest
TheGranger(1969)approachtothequestionofwhetherXcausesYistoseehowmuc hofthecurrentYcanbeexplainedbypastvaluesofY andthentoseewhetheraddinglagged valuesofXcanimprovetheexplanation.YissaidtobeGranger- c a u s e d byXifXhelpsinthepredictionofY,orequivalentlyifthecoefficientsonth e l aggedXarestatisticallysignificant.Notethattwo- waycausationisfrequentlythecase;XGrangercausesYandYGrangercausesX.
TodaandYamamoto ( 1 9 9 5 ) introducedthe T Y version ofGrangernon- causality testo n t h e p a r a m e t e r matricese v e n i f t h e p r o c e s s e s m a y b e i n t e g r a t e d o r cointegratedo f a n a r b i t r a r y o r d e r I t c a n b e a p p l i e d w i t h o u t p r e t e s t i n g f o r c o i n t e g r a t i o n anddoesnotrequireuseofanestimatedcointegrationeq uationintotheanalysis.
TY procedureemploysamodifiedWaldtestfor restrictionontheparametersoftheV A R (k).ItfollowsanasymptoticChi- squaredistributionwithkdegreesoff r e e d o m ( 2 (k))
(i) Determiningthe maximalorder(d ma x) of i n t e g r a t i o n of variables byusing theADFtest,PPtestwiththenullhypothesisisnon- stationary;aswellastheKP S S testwiththenullisstationary.It'sgoodtohaveacross- check.
(ii) EstimatingVARatlevelofvariablesandchoosetheoptimumlaglength(k)throug htheusualinformationcriteria,suchasAIC,SIC,SB,HQ,MAIC.
(iii) EstimatinganaugmentedVAR(k+dmax)inlevelsofvariablesandmakingt h e r e s i d u a l t e s t s u c h a s a u t o c o r r e l a t i o n , h e t e r o s c e d a s t i c i t y tom a k e s u r e t h i s V A R isstable.
(iv) ConductstandardWaldtestonthefirstkparametersofothervariableintheVA R ( k+ d) Ifsignificant,thenrejectnullofnon-causality.
Thenullhy po th esis ofn oGrangercausalitybetween Loil,Lex and Lv ni and the directionofGrangercausalitycanbedetectedbyapplyingstandardWaldtestst othefirst‘k’VARcoefficientmatrix.
Whena c o i n t e g r a t i n g r e l a t i o n s h i p e x i s t s a m o n g a s e t o f v a r i a b l e s , t h e n a n e r r o r co r r e ct i o n model(ECM)canbesetuptoreflecttheshort-runandlong- runrelationshipofthesevariables.
Anerrorcorrection model(ECM)is adynamicalsystem withthecharacteristics thatthedeviationofthecurrentstatefromitslong- runrelationshipwillbefedintoitsshort-rundynamics.
Anerrorcorrectionmodelisnotamodelthatcorrectstheerrorinanothermodel.E rr o r CorrectionModels(ECMs)areacategory ofmultipletimeseriesmodelsthatd i r e c t l y e s t i m a t e t h e s p e e d a t w h i c h a d e p e n d e n t v a r i a b l e r e t u r n s t o e q u i l i b r i u m afterachangeinanindependentvariable ECMsareatheoretically-drivenapproachu s e f u l f or es ti mat in g b o t h sho rt - te rm an d l o n g - t e r m effects o f o ne times e r i e s o n a n o t h e r Thus,theyoftenmeshwellwithourth eoriesofpoliticalandsocialp ro cesses.
Grangertwo- stepmethodologyasfollow.Inthefirststep,theoryandeconometricevidencea r e u s e d t o d e t e r m i n e w h e t h e r t h e d a t a c o n t a i n u n i t r o o t s i n t h e i n d i v i d u a l ti meseries.Iftheycontainunitrootornonstationary,theanalystestimatesthelong- runr e l a t i onship,β,inafirst- stepstaticcointegratingregressionofyonx,wherexmaybeavector: yt= α+βxt+ àt
Iftheresidualsfromthecointegratingregressionarestationary,thenthetimeseriesa r e sa idtobecointegratedandwemayproceedwiththesecond- stepregression.Int h e s e c o n d s t e p , c h a n g e s i n y a r e r e g r e s s e d o n c h a n g e s i n x a n d t h e p r e v i o u s p er i o d’ s equilibriumerror(theresidualsfromth ecointegratingregression)toestimatetheequilibriumrate,γ,andshort-rundynamics,λ 2 :
BasedonGranger(1987),model(1)canbechangedintoECMlikeequation7,inw hi ch combinetheshort- runrelationshipandlongrunrelationshipbetweenstockmarket,exchangeratean doilprice.
Where: γ 0 Intercept γ 01captures theshorttermeffectsofLoilinthepriorperiodonLvniinthecurrentp er i o d γ 02c a p t u r e s theshorttermeffectsofLexinthepriorperiodonLvniinthecurrentperi od. γ 03captures therateatwhichthesystemLvniadjuststotheequilibriumstateafterashock.Inot herwords,itcapturesthespeedoferrorcorrection. u t-1is theoneperiodlaggederrorcorrectionterm.
Researchingresult
Descriptivestatistics
Table4.1presentsthedescriptivestatisticsofthreevariables,exchangerate,crude oilpricesandVietnamindexintheentiresampleandeachphase.Itshowssomesd escriptiveitems u c h as:mean,median,maxium,minium, standarddeviation,skewness,Kurtosis,Jarque-
Standarddeviation(std.Dev)isameasureofdispersionorspreadintheseries. Thestandarddeviationisgivenby:
Skewnessi sa measureo f a s y m m e t r y o f t h e d i s t r i b u t i o n o f t h e s e r i e s a r o u n d i t s mean.Skewnessiscomputedas:
Where𝜎̂isa n e s t imatorf o r t h e standardd eviationt h a t i s b a sedo n t h e b i a sed estimatorforthevariance(𝜎̂=�√(𝑁−1)/𝑁).Theskewnessofasymmetric distribution,suchasthenormaldistribution,iszero.Positiveskewnessmeansthat thedistributionhasalongrighttailandnegativeskewnessimpliesthatthedi str ib ut io nhasalonglefttail.
Where𝜎̂isagainbasedonthebiasedestimatorforthevariance.Thekurtosisofthe normaldistributionis3.Ifthekurtosisexceeds3,thedistributionispeaked
(leptokurtic)relativetothenormal;ifthekurtosisislessthan3,thedistributionisf l a t (platykurtic)relativetothenormal.
Beraisateststatisticfortestingwhethertheseriesisnormallydistributed.T h e teststati sticmeasuresthedifferenceoftheskewnessandkurtosisoftheseriesw i t h thosefr omthenormaldistribution.Thestatisticiscomputedas:
B e r a s t a t i s t i c e x c e e d s (inabsolutevalue)theobservedvalueunderthenul lhypothesis— asmallp r o b a b i l i t y val ue l ea d s to t h e r e j e c t i o n o f t he n u l l h y p o t h e s i s o f a n ormaldistribution.Fort he LWAGEse ri es d i s p l a y e d abo ve, we r eje ct the h ypothesisofnormaldistributionatthe5%levelbutnotatthe1%significancelevel.
Intheentiresample,thefluctuationofexchangerateislowestinthethree(standardd e v i at i o n ofLEX=0 051733) Standarddeviations ofLoilandLvniare sameata b o u t 0.128.TheskewnessvaluesofLexandLoilarenegative,indicates thatthet ai l onthe leftsideofthe probability densityfunctionis longerorfatter thant her ig ht side.Conversely,theskewnessvalueofLvniispositive,indicatesthatthetailo ntherightsideoftheprobabilitydensityfunctionislongerorfatterthantheleftsi de.T h e K u r t o s i s e q u a l s 1 2 6 l e s s t h a n 3 , s o d i s t r i b u t i o n i s f l a t ( p l a t y k u r t i c ) relativetothenormal.Jarque-
Table4.1Descriptivestatisticofthreevariables,exchangerate,crudeoilpriceand VNind exfortheentiresample.
2007,thevolatilityofstockpricesislargest(standardd e v i a t i o n is0 1 7 0 7 2 2 ) While,t h e c h a n g e s o f e x c h a n g e r a t e s a n d o i l p r i c e s a r e smallrespondingto thestandarddeviationsare0.002598and0.061011respectively.T h e exchangerateandst ockpriceshaveleft-skeweddistributionandthecrudeoilp r i c e hasright– skeweddistribution.TheKurtosisvaluesofLoilandLexarelessthan3 , s o their d i s t r i b u t i o n i s f l a t ( p l a t y k u r t i c ) r e l a t i v e t o t h e n o r m a l a n d t h e KurosisvalueofLvniexceeds3,soitsdistributionsispeakedtothenormal.Jarque-
2009,allthreevariableshavesignificantchanges.Inparticular,thelargestoneiscrudeo ilpricewiththestandarddeviationis0.15736,thesecondoneisVNindexwiththestand arddeviationis0.128107,andthelastonei s t h e exchangeratewith thestandarddeviationis0.011895.The exchangerateands t o c k priceshaveright- skeweddistributionandthecrudeoilpricehasleft– skewedd i s t r i b u t i o n TheKurtosisvaluesofLoilandLvniarelessthan3,sothe ir distributionisflat(platykurtic)relativetothenormalandtheKurosisvalueofLexex c eed s 3,soi t s d i s t r i b u t i o n s i s pea ked toth en or ma l J a r q u e -
2014Q3,thevolatilityofexchangeratesishighestinth ree p h a s e s w i t h t h e s t a n d a r d d e v i a t i o n i s 0 0 2 1 3 5 3 While,t h e c h a n g e s o f o i l p r ic es andVnin dicesaresmallrespondingtothestandarddeviationsare0.064969an d 0.051253respec tively.Theallthreevariableshaveleft– skeweddistribution.AllKu r t o si s valuesofthreevariablesarelessthan3,sotheirdistribut ionisflat(platykurtic)relativetothenormal.Jarque-
Thelastphase,thevolatilityofoilpricesislargest(standarddeviationis0.120487).While,th echangesofexchangeratesandstockpricesaresmallrespondingtothestandardd eviations are0.003913and0.020221respectively.Theexchangerateando i l priceshaveright- skeweddistributionandthestockpricehasleft- skeweddi str ibut ion Kurtosisvaluesofthreevariablesarelessthan3,sotheirdistribution isfl at (platykurtic)relativetothenormal.Jarque-
Beratestsindicatethatdistributionso f Lex,Loil,andLvniarenotnormal.(seethetable4.2)
Table4.2Descriptivestatisticofthreevariables,exchange rate,crudeoilpriceandV N index forfour phases.
Unitroottest
Instatistic,i f a t i m e s e r i e s i s n o n - s t a t i o n a r y , t h e n i t c a n s t r o n g l y i m p a c t t o i t s b e h a v i o r andproperties. Forexamples,thepersistenceofshockswillbeinfinitefornon-stationary series.Iftwo variablesare trendingovertime,a regressionof oneont h e o t h e r c o u l d h a v e a h i g h R 2e v e n i f t h e t w o a r e t o t a l l y u n r e l a t e d I t makesregr essio n s p u r i o u s B e s i d e s , i f t h e v a r i a b l e s i n t h e r e g r e s s i o n m o d e l a r e n o n - stationary,thenitcanbeprovedthatthestandardassumptionsf o r asymptoticanalysiswill notbevalid.Inotherwords,theusual“t-ratios”willnotfollowat- d i s t r i b u t i o n , sowe cannotvalidly undertake h y p o t h e s is tests ab o u t t h e regression parameters.
Unitr o o t t e s t s c a n b e u s e d t o s u g g e s t h o w t o transformt h e d a t a a n d c h o o s e t h e a pp r e ci a t e regressionfunction.Moreover,economicandfinancetheoryoften suggeststheexistenceoflong-runequilibriumrelationshipsamongnon- stationaryt i m e seriesvariables.IfthesevariablesareI(1),thencointegration techniquescanbeusedtomodeltheselong-runrelations.Hence,pre- testingforunitrootsisoftenaf i r s t stepinthecointegration modeling.Inthisstudy, weusethreeunitroottests su ch astheaugmentedDickey–
Fullertest(ADF),thePhillips–Perrontest(PP)andKw iatkow ski –Phillips–Schmidt– Shintests(KPSS).
Fullertestforalargerandmorecomplicated setoftimeseriesmodels.T h e ADFs tatistic,usedinthetest,isanegativenumber.Themorenegativeitis,thestrongertherejec tionofthehypothesisthatthereisaunitrootatsomelevelofconfidence.T h is is mor enegative t h a n the t ab ula te d critical val ue of− 3 50, soa tthe 9 5pe r cen t leve lthenullhypothesisofaunitrootwillberejected.
Perront e s t (nameda f t e r PeterC B P h i l l i p s andPierreP e r r o n )isa unitr o o t testu s e d i n times e r i e s analysist o t e s t t h e nullh y p o t h e s i s t h a t a timeseriesis integratedoforder1.ItbuildsontheDickey–Fullertestofthenull hypothesisρ=0,in∆yt=ρyt-
Perrontestaddressestheissuethattheprocessgeneratingdatafory tmight haveahigh erorderofautocorrelationthanisadmittedinthetestequation—makingyt-
1en d o g en o u sandthusinvalidatingtheD i c k e y –Fullert- test.WhilsttheaugmentedDickey –
Fullertestaddressesthisissue byintroducinglagsof∆y tas regressorsinthetestequation, thePhillips–Perrontestmakesa non-parametriccorrectiont o t h e t - t e s t s t a t i s t i c T h e t e s t i s r o b u s t w i t h respecttounspecifiedautocorrelat ionandheteroscedasticityinthedisturbancep ro cess ofthetestequation.
TheADFandPPunitroottestsareforthenullhypothesisthatatimeseriesytisI( 1 ) S t a t i o n a r y tes ts, o n t h e o t h e r h a n d , a r e f o r t h e n u l l t h a t ytisI ( 0 ) T h e mostc ommonlyu s e d s t a t i o n a r y t e s t , t h eK P S S t e s t,i s d u e t o K w i a t k o w s k i ,
P h i l l i p s , SchmidtandShin(1992).Bytestingboththeunitroothypothesisandthestationa ryh y p o t h e s i s , onecandistinguish series that appeartobestationary, seriesthatappearto haveaunitroot,andseriesforwhichthedata(orthetests)aren otsufficientlyinformativetobesurewhethertheyarestationaryorintegrated.
Thetables4.3and4.4showtheresultsofunitroottestofthreevariableinmodelbyt h r e e metho dA D F ( A u g m e n t e d D i c k e y - F u l l e r ) , P P ( P h i l l i p s -
&trendinentiresamplesandforfourphasesAllvariablesa r e stationaryatfirstdifferent(I(0)inentiresamplesandinfourphases.Itimpliesthatwecannotusethesevariablesatl evelinthenormalregressions,becauseitwillmakethemodelspurious.Inthesection4.5,the nonlinearcointegrationsareusedtotestthelongrunrelationshipbetweencrudeoilprice,stockp riceandexchangerate.
GregoryandHansenTest-GHtest
Thea s s u m p t i o n t h a t t h e c o i n t e g r a t i n g r e l a t i o n s h i p r e m a i n s t h e s amed u r i n g t h e en t i r e p e r i o d s oft h e empiricals t u d y i s o f t e n v i o l a t e d d u e t o thee x i s t e n c e o f structuralbreaksina longt i m e series.T h e structuralb r e a k s c a n comef r o m t h e significanteventssuchasthefinancialcrisis,technologic alshocksorpolicyc h a n g e s …
GregoryandHansen(1996)introducedacointegrationtestincludingthei m p a c t ofthese eventsproxiedbythestructuralbreaks.ThenullhypothesisoftheG H t e s t i s n o c o i n t e g r a t i o n b e t w e e n v a r i a b l e s a n d t h e a l t e r n a t i v e hypothesist h a t th er e i sonebreakinthecointegration vector.T h a t is,existingalong– runrel at i onsh ip betweenstockmarket,exchangerateandcrudeoilpricesinVietnam.
Table4.5presentstheresultsofGHtestofthreevariables,crudeoilprices,stock pricesandexchangesratesinentiresampleandfourphases.Theteststatisticsinthetable4.5a rethesmallestvaluesoftheADF*,Z*ta n dZ*αs t a t i s t i c s Thesevaluesa r e compare dwiththecriticalvaluesintable4.6.IfthethesmallestvaluesoftheAD F * , Z * ta n dZ *αs t a t i s t i c sa r e b i g g e r thant h e i r c r i t i c a l v a l u e s , t h e n t h e n u l l hypot hesiscanbereject.
Table4.5Thresholdcointegrationresults lvni=f(loil,lex) EntireSa mple PhaseI PhaseII PhaseIII PhaseIV
Theresultpresentedintable4.5showthatthenullhypothesisisrejectedatsignificantlevel 5%fortheentiresamples.That is,thereexiststhelongrunrelationshipb e t w e e n c r u d e o i l p r i c e , s t o c k p r i c e s a n d e x c h a n g e r a t e I n t e r e s t i n g h o w e ve r , infourphases,thenullhypoth esiscannotberejectedatsignificantlevel5%.T h i s d o e s p r o v e t h a t e v e n t s i n t h e r e s e a r c h s t a g e i m p a c t i n g t h e l o n g - t e r m structureofoilpricesandthestockmarket.Theinterruptionsmakethemimpossibleto reachtheequilibriuminthelimitedtimeofsubsample.
TYprocedureofGrangernon–causalitytest
The study investigates the non-stationary nature of crude oil prices, stock prices, and exchange rates To analyze the Granger non-causality among these variables, I utilize the Toda-Yamamoto (1995) approach, which assesses the predictive ability of one time series based on the past values of another This method aims to determine if prior crude oil prices can forecast future stock prices or if crude oil prices Granger-cause stock prices Additionally, I plan to cross-check the results of the Granger non-causality test with those from cointegration tests, as the presence of cointegration between two or more time series implies that Granger causality exists in at least one direction, although the reverse is not necessarily true.
Table4 7 p r e s e n t s t h e r e s u l t s o f T - Y v e r s i o n o f G r a n g e r n o n - c a u s a l i t y tests h o w thatt h e s t o c k p r i c e s a r e e x p l a i n e d byp a s t m o v e m e n t s i n c r u d e o i l s t o c k s a n d exchangerates.Thenumbersinparenthesesprese ntthep-valueofChisquaretest.
Inthe entire sample, there isa unidirectionalGranger causalityrelationship runningf r o m the c r u de o i l p r i c e s t o V i e t n a m stock market( χ 2= 4 8 1 9 9 2 5 a n d p - v a l ue = 0 0 0 0 0 )
Inthefirstphase,the crudeoilpricesandtheexchangeratesdon’tGrangercausetoVietnams t o c k m a r k e t B u t t h e r e i s a n e v i d e n c e s h o w i n g t h a t s t o c k p r i c e s c a n G r an g e r causetoexchangerates(χ 2= 10.96704andp-value=0.0119).
Inthelastphase,thereisonlyonedirectionofGrangercausality,runningfromoilp ri ce toexchangerateatχ 2= 10.96703andp- value =0.0042.I n contrasttomyexpectation,thecrude o il price insignifican tlydoesG r a n ge r cause tostockprice.T h e effectsofoilpriceonstockmarketm aybeneedseverallagsandthisphaseisn otlongenoughtoseethem.Someindustriestak ebenefitsandsomeindustriesbeardamagesfromt h e d e c l i n e o f o i l p r i c e s , may bet h e r e h a s t h e b a l a n c e b e t w e e n b e n e f i t s anddamagesinthisperiod.
TheresultsoftheGrangernon- causalitytestshowthattherearenotanyGrangerc a u s a l i t y directionsrunni ngfromthestockmarketandexchangeratetocrudeoilp r i c e Thisindicatescrudeo ilpriceisanexogenousvariable.Exchangeratedoesn’tG ran ger causetostockmarketinthe entireresearchperiodandallphases.
Errorcorrectionmodel
Thesev a r i a b l e s o i l p r i c e s , s t o c k p r i c e s a n d e x c h a n g e r a t e s a r e s t a t i o n a r y a t f i r s t differenceandtheyarecointegratinginthelongterm.AccordingtoGranger(19 87),w ecanusetheerrorcorrectionmodel(ECM)toexploreimpactofcrudeoilprices,e x ch an g es ratesonstockpricesaboutthemagnitude,directionortheadjustedspeedo fstock pricestoreturntheequilibriumifhavingashockinpresent.
∆Lvni t Coefficient Std.Error t-Statistic Prob.
Watsonstatistic(0.010089