IMPACT OF OIL PRICE SHOCKS AND EXCHANGE RATE VOLATILITY ON .
P-ISSN: 2087-1228E-ISSN: 2476-9053Binus Business Review, 7(2), August 2016, 171-177DOI: 10.21512/bbr.v7i2.1453IMPACT OF OIL PRICE SHOCKS AND EXCHANGE RATEVOLATILITY ON STOCK MARKET BEHAVIOR IN NIGERIAAdedoyin Isola Lawal1; Russel O. C. Somoye2;Abiola A. Babajide3Department of Accounting and Finance, Landmark University,P.M.B 1004, Ipetu Road, Omu Aran, Kwara State, 251101, Nigeria2Department of Accounting, Banking & Finance, Olabisi Onabanjo University,Ago Iwoye, Ogun State, 120107, Nigeria3Department of Banking and Finance, Covenant University,KM. 10 Idiroko Road, Canaan Land, Ota, Ogun State, 112233, Nigeria1lawal.adedoyin@lmu.edu.ng; 2,3adedoyinisola@gmail.com1Received: 17th June 2015/ Revised: 25th July 2015/ Accepted: 26th July 2016How to Cite: Lawal, A.I., Somoye, R.O.C., & Babajide, A.A. (2016). Impact of Oil Price Shocksand Exchange Rate Volatility on Stock Market Behavior in Nigeria. Binus Business Review, 7(2), STRACTThe impact of exchange rate and oil prices fluctuation on the stock market has been a subject of hot debateamong researchers. This study examined the impact of both the exchange rate volatility and oil price volatility onstock market volatility in Nigeria, so as to guide policy formulation based on the fact that the nation’s economywas foreign induced and mono-cultured with heavy dependence on oil. EGARCH estimation techniques wereemployed to examine if either the volatility in exchange rate, oil price volatility or both experts on stock marketvolatility in Nigeria. The result shows that share price volatility is induced by both the exchange rate volatilityand oil price volatility. Thus, it is recommended that policymakers should pursue policies that tend to stabilize theexchange rate regime on the one hand, and guarantee the net oil exporting position for the economy, that marketpractitioners should formulate portfolio strategies in such a way that volatility in both exchange rates and oil pricewill be factored in time when investment decisions are being made.Keywords: oil prices, exchange rate, share prices, volatility, EGARCHINTRODUCTIONThe Arbitrage Pricing Theory (APT), accordingto Ross (1976), provides the theoretical backgroundthrough which multifactor framework is factoredinto stock market price determination and volatilitymechanism. Ever since 1976, when the theory waspropounded, some literatures have inquired into stockmarket behaviors using some variables. The theorypredicts that any anticipated or unanticipated arrival ofnew information about macroeconomic fundamentalswill exert on stock price behavior through theexpected dividends, discount rate routes or both. Thisstudy intends to inquire into the volatility of the stockmarket as induced by volatility in the exchange rateand volatility in oil price using monthly data sourcedon the Nigerian economy from 1985-2014. Babajide etal. (2015) observed that understanding this relationshipis crucial and important to virtually all the variouseconomic agents. For the investors, on the one hand,insight from this relationship can be used to constructportfolio strategies. On the other hand, policy makerswill find this knowledge of inestimable value as it willhelp in analyzing the transmissions channel betweenthe variables, thus aid better policy formulation.According to Basher et al. (2012), the existingliteratures on the relationship between the threevariables i.e. stock market prices, oil prices, andexchange rate can be broadly divided into two strands.The first strand deals with literature on the relationshipCopyright 2016171
between the two strands of literature is yet to beexplored especially from the emerging economiesperspective. This becomes needful now given thecurrent economic situation Nigeria finds herself.First, the nation is a mono-cultured economy withheavy dependence on oil. Second, the nation isbewitched with exchange rate difficulty. Fluctuationsin any of these sectors can send signal to other sectors.Furthermore, Chinzara (2011) classified studies thatinquired into the relationship between stock marketand macroeconomic variables (exchange rate and oilprices inclusive) into two categories, the first set ofliterature studies the relationship at first moment strandusing models like VAR, multivariate co integration,Autoregressive Distributed Lag, among others. Thesecond set of literature studied the relationship atsecond moments based on the understanding that sincethere is a strong connection between stock marketand the macroeconomic variables, volatility in themacroeconomic variables will exert on stock marketbehaviour. It is believed that studying the relationshipbetween macroeconomic variables and the stockmarket prices at the second-moment framework yieldbetter result required for meaningful policy formulationbecause it is the volatility of macroeconomic variablesthat make stock market planning difficult (Hsing,2011; Babajide et al., 2016a; Babajide et al., 2016b).Most of the literatures that inquired into therelationship using data from the Nigerian economyemployed first-moment approach (Somoye & Ilo,2008; Ologunde et al., 2006; Okoro, 2014; Gunu &Kilishi, 2010). The article tends to advance literatureby inquiring into the relationship between the threevariables from the second-moment strand. Thequestion are does exchange rate volatility exert onstock market volatility in Nigeria? Does oil pricevolatility exert on stock market volatility in Nigeria?How volatile is the Nigeria stock market? These arethe issues that this paper wants to address.The rest of the article is as structured afollows: Section 2 provides the literature review;Section 3 presents the data and the methodologyemployed, Section 4 presents the interpretation ofresults while Section 5 concludes the study and offersrecommendation for policy formulation.As noted by Basher et al. (2012), the literaturesexamined the connection between oil price, exchangerate and stock market prices can be broadly dividedinto two streaming literature viz: literature on therelationship between oil price and stock price on theone hand; and literature between oil price and exchangerates on the other hand. The authors submitted thatliterature on the connection between these two classesoil price - stock prices; and oil price - exchange ratenexus is very rear. Several recent literatures haveexamined the relationship between stock marketand some selected macroeconomic variables, andbetween stock market volatility and oil price volatilityespecially for the developed economies. Some of theseliteratures are briefly examined here.For the South African economy, literatures thatexamined the relationship between the stock prices,exchange rate, and oil price can be found in a numberof works, for instance, Jefferis and Okehalam (2000)examined the relationship between stock price andsome macroeconomic variables for South Africa,Zimbabwe, and Botswana. Their result shows that apositive relationship exists between the stock marketand real exchange rate. Chinzara (2011) observed thatvolatility in the exchange rate have a significant impacton stock market prices in the South Africa economywhile the impact of oil price on the stock market isless important. Hsing (2011) observed that negative,inconsequential relationships exist between nominaleffective exchange rate and South Africa stock marketindex. Gupta and Modise (2011) observed that apositive relationship exist between stock price andworld oil price for the South Africa economies.For the Chinese economy, Rong-Gang Conget al. (2008) examined the interactive relationshipbetween oil price volatility and the Chinese stockmarket from the period 1996-2007 using VARestimation techniques and observed that oil pricevolatility have no significant impact on stock returns.However, the authors further observed that oil pricevolatility does have negative impact on share prices ofoil companies on the floor of Chinese stock exchange(Hamma et al., 2014 ; Tsai, 2015).Malik and Ewing (2009) examined thevolatility transmission between oil prices and stockmarket prices on sectoral basis for the US economyfor the period 1992-2008 using BEKK-GARCH (1,1)and observed that there exist significant transmissionof stock volatility flow from oil price to the varioussectors studied.Oberndorfer (2009) examined the relationshipbetween the development of the energy market, priceof energy and stock prices in Eurozone from 2002-2007using ARCH and GARCH estimation techniques, andobserved that a negative connection exists betweenoil stock market return and price volatility for theEurozone.Aloui and Jammazi (2009) used Markovregime switching estimation techniques to examinethe conditional correlations and volatility spill overbetween stock market and crude oil index for theeconomies of France, Japan and UK for the periodof 1998-2009, and observed that increase in oil priceshocks significantly influence stock market volatilityfor the three economies (Aloui et al., 2014 ; Stavroset al., 2014 ).For the GCC’s economies of Kuwait, SaudiArabia, Qatar and UAE, Hammoudeh et al. (2009)used VAR-GARCH model to examine the volatilitytransmission and dynamic volatility between stockmarkets and oil in these economies. Their results showthat own past volatility is more significant than pastshock and that moderate volatility spill over existsbetween the sectors within the individual’s countriesexcept for Qatar. Their results is supported by Fayyadand Daly (2011) who observed that Qatar, UAE andUK indicates stock returns response to oil volatility172Binus Business Review, Vol. 7 No. 2, August 2016, 171-177
than other economies (Kuwait, Oman, UAE, Bahrain,Qatar, the UK and the US) studied (Arouri et al., 2011;Arouri et al., 2012; Awartani & Maghyereh, 2013).Similarly, Chuanguo and Chena (2011) usedARJI (-ht)- GARCH models to estimate data sourcedfrom 1998-2010 on Chinese economy to investigatethe impact of global oil price volatility on the Chinesestock market and observed that a positive relationshipexist between world oil prices and China’s stock return(Li et al., 2012; Liao, et al., 2015)Fillis et al. (2011) advanced literature by usingDCC-GARCH model to enquire into the time – varyingcorrelation between stock market prices and oil pricesfor both oil importing and exporting economiesbetween 1997 and 2009 and observed that a negativerelationship exists between oil price, and all the stockmarket investigated except for the 2008 financial crisisera (Sadorsky, 2012; Basher et al., 2012; Mollick &Assefa, 2013).The relationship between exchange and stockprices fluctuation can be traced to the works of Agrawal(2010) who examined the correlation between the dualusing developed economies data. Later on BahmaniOskooe and Sohrabian (1992) used cointegrationestimation techniques to examine the relationshipbetween the two variables and documented that abi-directional causality exist between the two in theshort run though no long run relation exists betweenthem. Similarly, Ajayi and Mougoue (1996) usedError Correction Model (ECM) and causality testto analyze daily data from 1985 to 1991 for eightdeveloped economies, and observed that upwardsshift in the domestic stock price impact negativelyon the domestic currency in the long run. They alsodocumented that currency depreciation (Exchangerate fluctuation) impacts negatively both at the shortand long runs on the stock market for the economiesstudied (Ajayi et al., 1998).For the Asian economies, Abdalla and Murinde(1997) observed that for the Indian, Korean andPakistani economies causality is from exchangerate fluctuation to stock prices movement; however,causality is from stock market to exchange for thePhilippines (Ho & Chia-Hsing, 2015). This contradictsSmyth and Nandha (2003) findings where the authorsstated that no relationship exists between the variablesin the long run for Pakistan, India, Bangladesh and SriLanka, though unidirectional causality exists betweenexchange rate and stock prices for Indian and SriLanka. Morley and Pentecost (2000) identified theimpact of exchange rate controls on the G-7 countriesin altering the relationship between the exchange rateand the stock market prices in 1980. Ibrahim and Aziz(2003) documented that a negative relationship existsbetween exchange rate and stock market for Malaysiabetween 1977 and 1998.Ozair (2006) observed that no causality nor cointegration exist between the two variables for the USeconomy, his findings were in line with that of Niehand Lee (2001) who discovered no significant causalityexist between the dual but contradicts Vygodina(2006) who established causality for large – cap stocksexchange rates. Pan et al. (2007) established theexistence of bidirectional causality between exchangeand stock price for Hong Kong before the 1997 Asiancries and a unidirectional causality between exchangerate and stock prices for the economies of Japan,Malaysia, Thailand, while Korea and Singaporeexhibit unidirectional relationship from stock prices toexchange rate (Sener et al., 2011). Agrawal (2010)observed that no correlation exists between the twovariables for the Indian economy using daily data fromOctober 2007 to May 2009, and that unidirectionalrelationship exist running from stock return toexchange rate (Takeshi, 2008).The preceding presents the review of empiricalliteratures on the volatilities of stock markets asinduced by oil price and exchange rate fluctuations.From the review it can be deduced that no significantwork has been done to examine the relationship usingdata from Nigerian economy, though Nigeria playssignificant role in global oil market and has the largesteconomy in Africa sub-region, thus, this study tendsto advance literature by investigating the relationshipbetween the trio so as improve decision making as perportfolio selection by investors on the one hand andgood policy formulation by policy makers on the otherhand especially now that the policy makers in Nigeriaare advocating for exponential economic growth cumwith eagerness of the stock market to recover fromthe losses of the recent global economic meltdown/financial crisis.Impact of Oil Price Shocks.(Adedoyin Isola Lawal, et al.)173METHODSThe data for this study were sourced from theCentral Bank of Nigeria Statistical Bulletin (variousissues). The data are in monthly form starting from1985 to 2014. The base year 1985 was chosen becausethat was the year data on All Share Index becameknown publicly in Nigeria, while 2014 was chosenbecause it is the month with most recent data as atdate. The All Share Index comprises of all the stockindexes on the Nigerian Stock Exchange, the data isreadily available from the Central Bank of NigeriaStatistical Bulletin. The Oil Price Index is the priceof the Nigerian crude oil (Bonny Light - Brent) at theinternational market, while the exchange rate is theprice of one Nigeria naira to the USD. Data on all thevariables were transformed into natural logarithms toachieve stationarity invariance.The model for this article is specified as follows:ASI f (OIL, EXC) (1)Where ASI is the All Share Index, which is aproxy of the stock market index, OIL is the proxy ofthe oil price index at the international market (Brent),and the exchange rate is the price of the Nigerian localcurrency to a US Dollar.Following Basher et al., (2012), the authors
expand equation (1) as follows:ASI α0 OILβ1 EXCβ2 µt(2)In achieving our goal of investigating the impactof the volatility of the exchange rate and oil prices onstock prices volatility, we employed the EGARCHestimation techniques.The EGARCH was developed by Nelson(1991) as an improvement on the earlier version of theGARCH models (Lawal et al., 2013, 2015; Babajideet al, 2016b), it is expressed as follows:whenand 0 (6)when(7)RESULTS AND DISCUSSIONSyear t;symbolizes the standardized shock for yeart. It can be seen that the number of standard deviationTable 1 presents the descriptive statistics of allthe variables used in this work. The authors employedthe Jarque-Bera (JB) test to examine the normalityof the time series used to know if the series followthe normal probability distribution. From the table,it can be deduced that the JB test result is large forall the variables; thus the authors concluded that thevariables are not normally distributed. In other word,the null hypothesis of normality for the variables canbe rejected.has deviated from its meanwhile symbolizes theerror term of a prediction model of a time series.Table 1 Descriptive Statistics of All the Variables(3)Whereyear t;Both therepresents the conditional variance foris the conditional volatility prediction forandimpact curve of the model. Therepresents the newsis the standardizedinnovation at t-1 and is usually centered atGiven thatis conditionally normal,the half normal distribution with the meanat t-1. 0.will followsuch thatis the absolute standardized innovationTo deepen the knowledge of the news impact ofthe model, Engle and Ng (1993) derive equation (3)as follows(4)By re-arranging the terms, it can be derived that:(5)MeanMedianMaximumMinimumStd. 0000315882,70,000000SumSum Sq. ,3Observations335335335Source: Authors’ computation from Eveiw 7.2The result of the correlation analysis is shownin the Table, from the result, it can be deduced thatboth negative and positive connection exist betweenthe variables. For instance, a positive relationshipoccurs between the All Share Index (ASI) and Oil price(OIL), while the relationship exhibits existence of anegative sign between All Share Index and Exchangerate (EXC).Table 2 Correlation Matrix ResultsIn this case,signifies a normal variateskewed to the left, while γ determines the degree ofskewness. By rearranging equation (5), the authorswill be able to resolve the combined impact of α and γin the results. Thus it can be derived ce: Authors’ computation from Eveiw 7.2174Binus Business Review, Vol. 7 No. 2, August 2016, 171-177
Table 3 ADF Unit Root ,0006201(0)Source: Authors’ computation from Eveiw 7.2the coefficient of γ though negative is not significant.This implies large stock in oil price volatility willincrease volatility in the stock market. The negativesign of – 0,046658 indicate that there is presence ofleverage effects in the series and that bad news on oilprice volatility exerts a larger impact on stock marketvolatility.CONCLUSIONS* 1% significant levelBased on the research in Table 3, it can bededuced that the unit root for all the variables arestationary at the level, since the critical values aregreater than ADF statistics. Thus the null hypothesisis rejected.Table 4 Results of the Volatility Measurementof the 0,8563090,00000,8313530,0000Source: Authors’ computation from Eveiw 7.2The coefficient of α is positive and significant at1% level of significant; this implies that large shocksof both positive and negative signs will lead to increasein volatility. The negative sign of the coefficient of γshows the existence of leverage effect, and that badnews has a larger impact on stock return volatility.The insignificant level of the coefficient of γ is anindication that the presence of leverage effect is notpronounced during the sample period. Th
The impact of exchange rate and oil prices fluctuation on the stock market has been a subject of hot debate among researchers. This study examined the impact of both the exchange rate volatility and oil price volatility on stock market volatility in Nigeria, so as to guide policy formulation based on the fact that the nation’s economy
4. Fiscal Shocks 111 4.1 Government Spending Shocks 112 4.1.1 Summary of Identification Methods 112 4.1.2 Summary of the Main Results from the Literature 114 4.1.3 Explorations with Several Identified Shocks 118 4.2 Tax Shocks 125 4.2.1 Unanticipated Tax Shocks 125 4.2.2 News About Future Tax Changes 132 4.3 Summary of Fiscal Results 134 5.
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