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The study investigated the relationship between crude oil price, exchange rate and sectoral stock prices in Nigeria from 2009 to 2016, using quarterly data collected from the Central Bank of Nigeria (CBN) and Nigeria Stock Exchange. Indices of the Nigeria stock exchange for three sectors (NSE Banking Sector, NSE Consumer goods and NSE Oil & Gas) were considered as dependent variables, which led to the specification of three models for the study.

The study implemented unit root with and without structural breaks to determine the order of integration and further applied a nonlinear ARDL (NARDL) which is an asymmetric extension of the standard co-integration test and the standard ARDL. The NARDL was applied to determine asymmetric effect of crude oil price shocks on stock prices.

Findings from the analysis indicated the presence of long-run co-integration in most cases and that positive and negative oil price shocks have differential effects on stock prices across sectors. Further, positive oil price shocks have greater impact on share prices in the banking and oil & gas sectors than negative oil price shocks of the same magnitude. Oil price shocks completely transmitted to the sectors, except consumer goods sector.

The study concluded that there should be close monitoring of the banking and oil & gas sectors as well as appropriate policy actions to curtail systematic risk in the banking industry.

Keywords:  Asymmetry, Nonlinear ARDL, Crude oil price shocks, exchange rate


Word Count: 225


 Content                                                                                                                                   Page

Title Page                                                                                                                               i

Certification                                                                                                                          ii

Dedication                                                                                                                             iii

Acknowledgements                                                                                                               iv

Abstract                                                                                                                                 v

Table of Contents                                                                                                                  vi

List of Tables                                                                                                                         vii

List of Figures                                                                                                                       viii

Appendices                                                                                                                            xi



  • Background to the Study 1

1.2      Statement of the Problem                                                                                           4

1.3      Objective of the Study                                                                                               6

1.4      Research Questions                                                                                                     6

1.5      Hypotheses                                                                                                                 7

1.6      Scope of the Study                                                                                                     7

1.7      Significance of the Study                                                                                           8

1.8      Justification for the Study                                                                                          8

1.9      Operational Definition of Terms                                                                                 11

Content                                                                                                                                   Page


2.1      Conceptual Model                                                                                                      12

2.2      Theoretical Framework                                                                                               23

2.3      Theoretical Review of Variables                                                                                 31

2.4      Empirical Framework                                                                                                  38

2.4      Gaps in Literature                                                                                                       56


3.1      Research Design                                                                                                         58

3.2      Population                                                                                                                   58

3.3      Data and Sources of Data                                                                                           58

3.4      Model Specification                                                                                                    59

3.5      Estimation Method                                                                                                     62

3.6      A priori Expectation                                                                                                   64

3.7      Ethical Consideration                                                                                                 65

3.8      Resources and Skills Needed for the Study                                                               65



4.1      Descriptive Statistics                                                                                                  66

4.2      Unit Root Test Results                                                                                               69

4.3      Bound Test Estimates                                                                                                 76

4.3      Discussion of Long-run and Short-Run Co integration                                              80

4.4      Post Estimation Test and Result                                                                                 95

Content                                                                                                                                   Page



5.1      Summary                                                                                                                     101

5.2      Conclusion                                                                                                                  104

5.3      Recommendations                                                                                                      104

5.5      Limitation of the Study                                                                                              106

5.6      Suggestion for Further Studies                                                                                   106

5.4      References                                                                                                                  107



Table                                                                                                                                      Page

4.1.1A            Descriptive Statistics before Transformation to Log                                      68

4.1.1B            Descriptive Statistics after Transformation to Log                                         69

4.2.1A            Unit Root without Structural Breaks before Transformation to Log             71

4.2.1B            Unit Root without Structural Breaks after Transformation to Log                72

4.2.2A            Unit Root with Structural Breaks before Transformation to Log                  74

4.2.2B            Unit Root with Structural Breaks after Transformation to Log                     75

4.3A               Bound Test Estimates for Model 6                                                                 77

4.3B               Bound Test Estimates for Model 7                                                                 78

4.3C               Bound Test Estimates for Model 8                                                                 79

4.4.1A            Normalized Long-Run Estimates for Model 6                                               82

4.4.1B            Short-Run Estimates for Model 6                                                                   84

4.4.2A            Normalized Long-Run Estimates for Model 7                                               86

4.4.2B            Short-Run Estimates for Model 7                                                                   88

4.4.3A            Normalized Long-Run Estimates for Model 8                                               91

4.4.3B            Short-Run Estimates for Model 8                                                                   94

4.6                  Ramsey Rest Test of Linearity                                                                       97


Figure                                                                                                                                                Page

4.5.3A            CUSUM Stability Test for NSEBNK                                                                        98

4.5.3B            CUSUM Stability Test for NSECONS                                                          99

4.5.3C            CUSUM Stability Test for NSEO&G                                                                        100




A        E-views Code to Generate Crude Oil Price Shocks

B        Unit Root without Structural Breaks, before Transformation to Log

C        Unit Root with Structural breaks before Transformation to Log

D        Descriptive Statistics before Transformation to Log

E        Descriptive Statistics after Transformation to Log

F        Unit Root after Transformation to Log without Structural Break Dates

G        Unit Root Result with Structural Breaks before Transformation to Log

H        Unit Root Result with Structural Breaks after Transformation to Log

I         Non-Linear ARDL, Short run and Long -run Results

J         LM Serial Correlation Test Result

K        ARCH LM Heteroschedasticity Test Result

L        Descriptive Statistics for Models



  • Background to the Study

Nigerian economy has relied heavily on importation of goods from foreign countries and has depended on crude oil generated revenue for over three decades. Crude oil revenue is the largest contributor to the Gross Domestic Product (GDP) in Nigeria, (CBN, 2015). The Nigerian government makes use of the international crude oil price as a benchmark price in budgetary preparations in the country. This implies that an oil exporting economy will experience boom when there is an increase in crude oil production and the crude oil market price exceeds the benchmark price set by government while the economy may some form of recession or sluggishness in the economy when the price falls below benchmark price Clifford K. (March 10, 2017). Such frictions may reflect in the form of inability of the government to fund the national budgets due to a reduction in foreign exchange earnings (Adaramola 2015) the recent situation in Nigeria during the periods that recorded low crude oil price, many states in the country were unable to pay salaries, exchange rate depreciated further and many people lost their jobs (Alechenu 2016, March 25).

Historical data collected from the CBN has shown that crude oil price began falling persistently since November 2013 and got to its lowest price in February 2016. The implications of this fall price reflected in the form of decline in revenue in Nigeria and as a result, most states could not afford to pay salaries and reduction in accumulated foreign exchange which is to be used for importation of consumer and capital goodsGabriel (June 15, 2015). This scarcity of foreign exchange led to a further depreciation in the National currency (Alechenu J. 2016, March 25).The Naira was fast approaching N500 to $1 and finally exceeded N500 to $1 in the parallel market between January and February 2017 (NAN, 2017, February 3). The naira was also traded for N617 and N527 for one Pound Sterling and Euro respectively. However, the naira is currently appreciating in the parallel market in Nigeria (NAN, 2017, February 3). Thus, this suggests that the implications of crude oil volatility and exchange rate volatility on the economy cannot be overlooked. This study investigated how crude oil price shocks and exchange rate affectssectoral stock prices in Nigeria.

The stock market is a place where most elements that gear the development of a nation’s economy operate with one another and it plays a prominent role in shaping a country’s economic and political development. It plays a major role in financial intermediation in both developed and developing countries by channeling idle funds from surplus to deficit units in the economy. This is because as the economy of a nation develops, more resources are needed to meet the need for its rapid expansion. The stock market serves as a channel through which savings are mobilized and efficiently allocated to achieve economic growth (Alile, 1984). Long term capital resources are pooled through issuing of shares and stocks by industries in dire need of finance for expansion purposes. Thus, the overall development of the economy is a function of how well the stock market performs.This is why empirical evidences from developed economies as well as some emerging markets have proved that the development of the stock market is sacrosanct to economic growth (Asaolu & Ogunmuyiwa, 2010).

Stock prices are generally believed to be determined by some fundamental macroeconomic variables such as interest rates, money supply inflation, exchange rate and Gross Domestic Product (GDP), hence, Change in the prices of stock can be linked to some macroeconomic behavior of both advanced countries and developing countries (Muradoglu, 2000). The relationship between exchange rate and stock price could be negative or positive, depending on whether the economy is export-or import-dominant, respectively. For an export dominant country, an increase in exchange rate would result in a decline in the country’s export competitiveness, thus has a negative impact on the domestic stock prices. For an import dominant country, on the other hand, an appreciation of exchange rate would reduce input costs, thus generates a positive effect on the domestic stock prices (Narayan & Narayan, 2010).

Variations in exchange rates affect the competitiveness of firms who borrow in foreign currencies to finance their operations and this is because changes in exchange rates affect the earnings as well as its cost of funds and hence its stock prices (Dornbusch & Fischer, 1980). An appreciation of the local currency makes exports less attractive and thus bring about a reduction in foreign demand and the total revenues for the firms and thus, bringing about a fall in the value of the exporting firm and its stock prices (Gavin, 1989).

The relationship between stock prices and macroeconomic variables is well illustrated by the theoretical stock valuation models which shows that the current prices of any equity share is approximately equal to the present value of all future cash flows discounted; hence, any macroeconomic variable that affect the cash flow and the required rate of return will certainly have significant effect on the share value as well (Adaramola, 2012). Hence, since macroeconomic fundamentals such as exchange rate and oil price volatilities can affect the cash flow or required rate of return, then it will equally have an effect on stock prices. Changes in exchange rates can significantly affect the competitiveness of firms as variations in exchange rate affects the value of the earnings as well as the cost of its funds and this is because many companies borrow in foreign currencies to finance their operations and hence its stock price (Dornbusch & Fischer, 1980).

Oil prices can act as the transmission channel through which the real exchange rate affects the stock market and as such, inferences about the long-run relationship of variables and the causality structure may not reflect the true impact of exchange rate on stock price without an inclusion of oil price as an explanatory variable(Narayan & Narayan, 2010). When Oil is considered as an input to production process, an increase in oil price will give rise to increased production costs which causes productivity to decline (Narayan & Narayan, 2010).

There is large number of available literature that studied relationship between crude oil price, exchange rate and stock prices in Nigeria and some of which includes Adaramola, (2012); Adebiyi, Adenuga, Abang and Omanukwe  (2014); Akinlo, (2014);Akomafe, Jonathan and Danladi, (2014); Abdulrasheed, (2014); Asaolu and Ilo (2012); Augustine, (2015) and Osuala & Ebieri, (2015).The findings of these studies were mixed. Abdulrasheed, (2014); Asaolu & Ilo, (2012); Augustine, (2015) showed that the relationship between Oil price, Exchange rate and stock price is positive while few others including Akinlo, (2014); Osuala and Ebieri, (2015) found a negative relationship between oil price and stock prices in Nigeria. Regarding causality, Adaramola, (2012) found a unidirectional causality from oil to stock market. Akomafe, et. al, (2014) found evidence of unidirectional causality from oil price to three different industrial sectors (banking sector stocks, construction sector stocks and oil & gas sector stock). Abdulrasheed, (2013) found no evidence of causality from exchange rate to stock price while Akinlo, (2014) showed that the causality flows from stock market to exchange rate not the reverse.  The observed mixed finding implies the need for further investigations in to the nature of relationship and the direction of relationship between exchange rate, oil price and stock prices in Nigeria. This study has its mainfocused in understanding the nature of the relationship between oil price, exchange rate and sectoral stock price indices(NSE Banking index; NSE Consumer goods index and NSE Oil & Gas index) in Nigeria.

  • Statement of the Problem

The source of government revenue in Nigeria has been from the oil sector for more than three decades, using the price of the product in international market as the bench mark price. Performance of successive government’s budget in Nigeria has based its budgetary preparations mostly on earnings from oil; hence the performance of the economy often becomes sensitive to the variations in crude oil production and its prices to provide the needed foreign currencies needed to support imports. In recent years, oil prices have not been stable thus having adverse effects on budgetary planning in Nigeria with serious consequences on the overall economy (Asaolu & Ilo, 2012). The over reliance of the economy on importation of virtually all goods including refined oil despite being the 5th largest exporter of crude oil in the world, has made the Nigerian economy more vulnerable to exchange rate volatility, despite the expectations that depreciating exchange rate is expected to boost exports (Dornbusch & Fischer, 1980). However, there is need to study the implications of depreciating exchange rate on stock prices in an imports dependent country like Nigeria.

Exchange rate and oil price are two strong prices and their volatility can transmit either negative or positive effects on stock market prices in Nigeria (Adaramola, 2012). Their volatilities threaten smooth operation of business and the economy and as such can affect the expected future cash flow of companies listed on the stock exchange market and this will reduce the value of the firm and hence the share price of the listed company (Asaolu and Ilo 2012). International Crude oil price fluctuations are observed to be accompanied by some variations in the general stock market performance, measured by the All Shares Index (ASI). In January 1986, crude oil price was as low as 25.62 dollar per barrel (dpb) while stock price (ASI) was 111.3. Over the years ASI has increased significantly with upward fluctuations in oil price. In November 2000 ASI has increased to 7, 164.4 while the oil price has increased to 34.26 and by December 2000 oil price has declined to 28.4 dpb while the ASI rises to 8,111.0. The year 2007 and especially 2008 experienced significant boom with high ASI stock market values. The February 2008 recorded the highest stock index 65,652.4 with a corresponding Oil price of 95.35 dpb. June 2008 has the highest oil price 134. 02 dpb considering from years between 1983-2016, with corresponding ASI of 55, 949.0 and after this price oil price began to fluctuate downward with its last highest value of 105 dpb in June 2014 the oil price depreciation is persistent and the lowest oil price 30.62 recorded in February 2016 while the ASI falls significantly to 24, 570.73. As at august 2016, oil price has risen to 44.8 dpb and ASI 27, 599.03 (CBN, 2010).

Fromthe foregoing there seems to be to be inconsistent relationship between oil price and stock price, in Nigeria is mixed. The data shows periods where crude oil price increases are accompanied by increases in stock prices, implying a positive relationship while at some other period a negative relationship is observed and this observation corresponds to the mixed findings of Adaramola, (2012); Adebiyi et. al, (2014) Akinlo, (2014);Akomafe, Jonathan & Danladi, (2014); Abdulrasheed, (2014); Asaolu & Ilo, (2012); Augustine, (2015) and Osuala & Ebieri, (2015). Thus, the essence of this study is to carry out further empirical investigation because of the to mix findings that exist regarding the effect of crude oil price, exchange rate and sectoral stock prices in Nigeria.

  • Objective of the Study

The main objective of this study is to empirically determine the effect of crude oil price shocks on sector stock prices in Nigeria. The specific objectives are to:

  1. determine the effect of oil price shocks on sectoral stock price indices(NSE Banking sectorindex; NSE Consumer goods sector index and NSE Oil & Gas sector index) in Nigeria;
  2. determine the presence of long-run co-integration relationship among oil price, exchange rate and sectoral stock price indices((NSE Banking sectorindex; NSE Consumer goods sector index and NSE Oil & Gas sector index) in Nigeria;
  3. determine the presence of asymmetry in crude oil price and their effects on sectoral stock prices indices(NSE Banking sectorindex; NSE Consumer goods sector index and NSE Oil & Gas sector index) in Nigeria;and
  4. determine the effect of exchange rate on sectoral stock price indices(NSE Banking sectorindex; NSE Consumer goods sector index and NSE Oil & Gas sector index) in Nigeria;


  • Research Questions

This study answered the following research questions:

  1. What is the effect of oil price shocks on sectoral stock priceindices(NSE Banking sectorindex; NSE Consumer goods sector index and NSE Oil & Gas sector index)in Nigeria?
  2. Is there long-run co-integration relationship among oil price, exchange rate and sectoral stock priceindices(NSE Banking sectorindex; NSE Consumer goods sector index and NSE Oil & Gas sector index) in Nigeria?
  3. Is there asymmetry between crude oil price and sectoral stock priceindices(NSE Banking sectorindex; NSE Consumer goods sector index and NSE Oil & Gas sector index) in Nigeria?
  4. What is the effect of exchange rate on sectoral stock price (NSE Banking sectorindex; NSE Consumer goods sector index and NSE Oil & Gas sector index) in Nigeria?


  • Hypotheses

Based on the objectives, the following hypotheses were germane:

Ho1: Crude oil price has no statistical impact on sectoral stock priceindices(NSE Banking

Sectorindex; NSE Consumer goods sector index and NSE Oil & Gas sector index)in


Ho2:There is no long-run co-integration relationship among crude oil price, exchange rate and sectoral stock indices(NSE Banking sectorindex; NSE Consumer goods sector index and NSE Oil & Gas sector index)in Nigeria

Ho3:      There is no Asymmetry betweenoil price shocks and sectoral stock indices(NSE Banking sectorindex; NSE Consumer goods sector index and NSE Oil & Gas sector index)in Nigeria

Ho4:     Exchange rate has no statistical impact on sectoral stock price indices(NSE Banking sectorindex; NSE Consumer goods sector index and NSE Oil & Gas sector index)in Nigeria.

The null hypotheses were tested at 5% level of significance.


  • Scope of the Study

This study examined the effect of exchange rate volatility and crude oil price shocks on sectoral stock price in Nigeria Stock Exchange using quarterly data from 2009.Q1 –2016.Q4.Three sectoral indices out of seven (7) stock indices of the Nigeria stock exchange. Exchange rate quarterly data is based on the average.

The three sectoral indices included in the study are banking, consumer goods, oil & gas Sectoral index from the Nigeria Stock Exchange Index. The All share index, NSE 30 Index, Lotus Islamic banking index and NSE Industrial goods were excluded from the study because the NSE 30 and ASI are aggregated stock prices of the stock market however; this study was primarily interested in disaggregated stock price and not aggregated stock prices in Nigeria. The lotus Islamic banking index is also not included because Islamic banking is a recent development in Nigeria and as such data for this variable is not available. NSE Industrial goods are also excluded from the analysis because the data is not available from 2009 which is period shorter than the other variables available. NSE Industrial goods is only available from 2012-2016 which implies lesser observation than the other 2 sectors.

  • Significance of the Study

It is important to know the effects of exchange rate, oil price on sectoral stock prices in Nigeria. Findings of the study would be helpful to government, investors and other stakeholders to understand how stock prices of different sectoral share prices of the Nigerian stock exchange would respond to variations in exchange rate and oil price volatility. This study is essential and helpful in giving better explanations to stock market behavior induced by oil price shocks and exchange rate. Exchange rate deterioration in Nigeria has been persistent for over 3 decades can have adverse effects on an import dependent nation. Similarly over dependence of the economy on crude oil revenue could have adverse effect on the economy when there is a significant increase in oil price since oil is used as an input to most businesses to Nigeria.

Findings from this study is helpful to Government in policy making and also to management of companies in banking sector, consumer goods sector and oil and gas sector to understand the implications of oil price shocks to their cash-flow, which equally impact on the share prices of the sectors to enable them properly hedge against risk emanating from crude oil price and exchange rate shocks. It would provide basis for government to make policies that would maintain stable oil price and supply to avoid volatility generated by shocks in the economy.

  • Justification for the Study

The exchange rate is an important relative price as it has influences on the external competitiveness of domestic goods. Given the import dependent nature of the Nigerian industrial sector, the continued depreciation of the naira exchange rate vis-à-vis the currencies of other major trading partners, means that more resource would be needed to increase domestic output. A depreciating exchange rate in the absence of domestic sources for input and inadequate infrastructure will raise the cost of production, which will in turn make locally produced goods less competitive compared to the imported goods, thus, reversing the benefit of cheaper exports expected from depreciation of any currency. This is because share prices are approximately the present value of all discounted future cash flows which can be affected by macroeconomic variables like exchange rate and oil price volatility.

There is limited literature that studied sector effects of crude oil volatility and exchange rate volatility on sector stock prices in Nigeria. Akomolafe, Jonathan, Danaladi, (2014) and Ohiorenoya, Iwedi and Igbanibo, (2015) did a sectoral analysis of stock prices covering 3 sectors listed in the Nigeria Stock Exchange but the study did not include exchange rate as an independent variable. The study also did not consider oil price shocks.

Many others including Osuala and Ebieri, (2015); Asaolu and Ilo, (2012) are similar to this study in terms of variables but they did not study disaggregate stock prices by sectors, they rather studied aggregated stock prices using All Share Index and how it responds to variations in exchange rate and crude oil but did not put volatility into consideration; they did not consider structural breaks and nonlinearity that may be present in variables which can undermine the predictive power of the model as stated by Dick and Panchenko, (2006) and can reduce the power of the model to reject the null hypothesis when structural break is present in the time series data.

The findings of Hiemstra and Jones, (1994) Hamilton (1996), Ciner, (2001) showed that crude oil price changes have nonlinear causal influence on stock market returns and thus, there is need for a non-parametric model that can explain relationship between crude oil price, exchange rate and stock prices in Nigeria. Nonlinear ARDL (NARDL) was implemented in this study to investigate nonlinear dependence between oil price and stock prices in Nigeria.

Several studies have applied the standard co-integration modeling and granger causality, error correction model and granger causality by means of standard times series techniques. Although these techniques enable evaluation of their long-run as well as their short-run interactions, however, they were built based on the presumption of symmetric relations between oil price and stock prices and such techniques are not adequate to capture potential asymmetries in the oil price dynamics. It is based on this Shin, Greenwood-Nimmo, (2011) advanced a nonlinear ARDL (NARDL) as an asymmetric extension to the well known ARDL model of Pasaran and Shin, (1999) and Pasaran et al. (2001) to capture long-run and short-run asymmetries in the variable of interest. This NARDL approach to co-integration can accommodate structural breaks in time series and just like the ARDL approach; NARDL is applicable to studies with small or finite sample size (Pasaran and Shin (2001). It applicable on series with less than 30 observations which makes the application of NARDL to this study adequate and appropriate since the variables in this study have less than 30 observations.

Thus, this study applied the recently developed NARDL developed by Shin et al (2011) to account for short-run and long-run asymmetries between crude oil price, and sectoral stock prices in Nigeria.


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