ABSTRACT
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.
TABLE
OF CONTENTS
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
CHAPTER ONE: INTRODUCTION
- 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
CHAPTER TWO:
REVIEW OF LITERATURE
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
CHAPTER THREE:
METHODOLOGY
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
CHAPTER FOUR: DATA ANALYSIS, RESULTS AND DISCUSSION OF FINDINGS
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
CHAPTER FIVE: SUMMARY, CONCLUSION
AND RECOMMENDATIONS
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
LIST OF TABLES
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
LIST OF FIGURES
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
APPENDICES
Appendix
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
CHAPTER
ONE
INTRODUCTION
- 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 goods Gabriel (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 affects sectoral stock prices in Nigeria.
A SECTORAL ANALYSIS OF CRUDE OIL PRICE, EXCHANGE RATE AND STOCK PRICES IN NIGERIA, (2009-2016)
