The Inflation And Stock Returns In Nigeria

This study empirically examines the relationship between inflation and stock returns in Nigeria during 1997-2006. The study focuses on different econometric models to investigation this relationship using monthly data of the All Share Price Index from the Nigerian Stock Exchange and Nigerian Consumers Index. The simple OLS regression result suggests that the residuals are stationary, which implies that stock returns and inflation are co integrated. Therefore we can conclude that there is a long run relationship between stock returns (LOGASI) and inflation (LOGCPI).The Engel co-integration results reveals that there is long run relationship between inflation and stock returns .the study further goes on to the determine the causal long run relationship using the Error Correction Model (ECM). This article offers evidence of a positive relationship between stock market returns and inflation. This result confirms that stock returns act as a hedge against inflation.

CHAPTER ONE

INTRODUCTION

1.1 Background to the Study

The advent of oil boom in Nigeria in the early 1970’s, has led to the instability of stock prices. This has been attributed to many factors such as: budget deficit monetization, inflow of foreign capital from crude oil sales and financial markets creation of excess private domestic credit.

Since early 1970’s, inflation rates in Nigeria has been highly unstable; the high inflationary change was in excess of 30 percent. This is evident in the high correlation of money supply growth and high inflation due to the fact that real economic growth is less in real term to money growth. This can be observed from the growth in money supply and some structural factors such as; supply shocks arising from famine, unfavorable terms of trade and devaluation of currency. Furthermore, Structural Adjustment Program (SAP) introduced by the government in the late 1980’s also accounted for the increase in price level in the economy. Consequently, inflation in Nigeria has overtime responded to structural changes. These changes can be characterized into four periods based on the pattern and events that occur at that period.

The first period of inflationary increase in Nigeria was noticed from 1974 to 1976; inflation increased by 30 percent. This inflationary pressure was as a result of the following:

High cost of agricultural produce caused by drought in the Northern part of Nigeria,

Excessive oil revenue monetization,

increase in wage rate based on the recommendation of the Udoji commission of 1974, Folawewo (2005), and political instability

The second period was from 1983 to 1985 when inflation rate reached 40 percent. This period noticed very little economic growth, The Nigerian government was under intense pressure from debtor groups to accept International Monetary Fund conditionality’s of devaluation of domestic currency because government debt has increased above 70 percent while excess money growth was around 41and 43 percent. This period also witnessed poor external trade performance.CBN (, 2006)

The third period was from 1987 to 1989 when inflation rate hovered around 35 percent. During this period, the economy experienced high inflationary pressure brought about by fiscal expansion noticed in the 1988 budget, the debt for equity swaps conversion method adopted by the Government of Nigeria and the drastic contraction in monetary policy, all accounted for this change that span through to the early 1990’s.

Finally, the fourth period occurred between 1993 and 2000, as a result of fiscal deficit expansion which caused a 70 percent increase in money supply with a knock-on effect on domestic credit of the private sector of the economy.CBN, (2006)

Overall, inflationary pressure can be largely attributed to structural factors such as; real income reduction caused by fluctuation in oil revenue, high nominal wages and debt obligation in form of expansionary fiscal deficit. These invariably mean that over the years, fluctuation in commodity price is a normal feature of the Nigerian economy.

One major commodity considered in this study is the capital market stock, i.e. the Stock market. Stocks listed in Nigeria are traded on the floor of the Nigerian Stock Exchange (NSE) while the Securities and Exchange Commission (SEC) is the apex regulatory body which oversees the activities and affairs of the major players on the floor of the Stock Exchange.

The Nigeria Stock Exchange was established in September 15, 1960 but commenced business on June 5, 1961 with 19 securities listed and traded on the Lagos Stock Exchange. Based on the recommendation of the Government Financial System Review Committee in 1976, the Lagos Stock Exchange was renamed and made part of the Nigerian Stock Exchange in December 5, 1977. The Nigerian Stock Exchange has nine branches established in major commercial cities in Nigeria. The main exchange of stocks of large enterprises are traded in the Nigerian Stock Exchange while small and medium scale enterprises are listed and traded in the Second tier Securities Market (SSM). From 1963 to 1990, the Nigerian stock exchange witnessed an overwhelming increase in government stock which exceeded the equities of industrial companies; however this trend changed from 1991. The value of equities of industrial companies increased to billions of Naira, while government stock traded on the Nigerian Stock Exchange was worth millions of Naira this decrease continues till date, a development to the deregulation of the economy.

Despite the increase in market capitalization noticed in the economy at that period, the ratio of this amount to the Gross Domestic Product and Gross Fixed Capital Formation was still low. This increase was between 4.8% and 25.4% for gross domestic product while the ratio for gross fixed capital formation is between 28% and 55% from 1963 to 1990 (CBN, 2006). The ratio of market capitalization in the gross domestic product and gross fixed capital formation increased geometrically from 1990 to 1995. Although there was decrease in the share of market capitalization in gross domestic product and gross fixed capital formation, the return on investment did not follow the same pattern. This decrease noticed at that period was caused by a banking crisis in which a total of 26 banks were liquidated in 1998. However, with the recapitalization of the banking sector in 2005, the industry remains the most active participant in Nigerian stock market up till date. The trend in Nigeria Stock Exchange causes the price and return on stocks to be highly volatile.

1.2 Problem Statement

Price stability is essential in determining whether an economy is stable or not. Inflation which is the constant increase in price creates uncertainty in the economy; uncertainty makes both domestic and foreign investors unwilling to invest. In Nigeria inflation has led to increase in nominal interest rates which affect the value of interest payment of banks and financial institutions. Furthermore, determination of the problem caused by inflation depends upon the degree in which inflation is anticipated correctly or not. If inflation is anticipated correctly and the monetary authority is seen to be credible, the fluctuation in price would be managed effectively but if inflation is unanticipated, some economic agents will gain while others will lose. Unanticipated inflation impact negatively on saving ability of the citizens and as a result, low saving leads to a fall in the demand for stocks and equities as financial wealth. This decrease in demand causes the price of equities to fall thereby reducing returns on equities and stocks.

Furthermore, the prices of stock determine how effective and efficient the stock market allocates shares and equities based on preference and availability of market information. Increase or decrease in price of stock create uncertainty for the investors and in turn affect the demand and supply of stocks. Therefore, general increase in price level may affect people’s potential investor’s investment decision which has negative impact on the total returns on stocks in the economy at large. This situation is prevalent in the Nigerian economy; therefore there is the need to examine the effect of inflation on stock returns and its implication on investment. The Fisher’s hypothesis (Fisher’s effect) suggests that stocks or equities hedge or evade inflation, empirical investigation suggest that inflation and stock returns are negatively related. This study will be looking at relationship between inflation and stocks in Nigeria.

The study of this relationship is essential in improving and in the understanding of stock markets, thus providing standards for decision-making about asset allocation.This study contributes to the existing literature by providing evidence for whether inflation affects stock returns both in the long run and in the short run.

1.3 Justification for the Study

Despite the large number of empirical studies on the relationship between inflation and stock returns, there is no general consensus on the causal direction of this relationship. Empirical works as; Nelson (1976), Shwarts (1977), Fama (1981), Geske and Roll (1983), Gultekin (1983), Marshall (1992), Bakshi & Chen, (1996), Zhao (1999), Chatrath et al (1997), Spyrou (2001), Omran and Pointon (2001), Crosby (2001), Gallagher and Taylor (2002) and Floros (2002), suggested a negative relationship between inflation and stocks while Boudoukh and Richardson (1993), Graham (1996) and Choudlery (2001) in different studies take the opposing view, i.e. that there exists positive relationship between inflation and stock returns.

However, most of these studies were carried out in industrial nations and some selected developing countries most especially Latin American countries. Specific studies on the exact relationship between inflation and stock returns in Nigeria have not been explored rigorously. Furthermore, considering the negative impact of inflation on prices of commodities in Nigeria coupled with the volatility of stock returns, this study seek to provide a rigorous analysis of the dynamics of inflation and its implication on stock returns in Nigeria using an Error Correction Model to create a parsimonious and encompassing model that would show both short-run and long-run relationship between inflation and stock returns in Nigeria.

1.4 Plan of Study

Following the introductory remarks in chapter one, chapter two will review the existing literature on this subject. While chapter three will focus on the theoretical framework, methodology, model specification, estimation technique and sources of data. The summary of result of the empirical analysis is presented in chapter four while the study will be rounded up in chapter five with summary of findings, policy implication and conclusion.

CHAPTER TWO

LITERATURE REVIEW

2.1 Introduction

Section 2.2 of this chapter discusses the underpinning theories of inflation and stock returns. Section 2.3 examines the empirical literature review on inflation and stock returns this is to help identify the link between inflation and stock returns. Finally section 2.4 examines the methodological literature on inflation and stock returns.

2.2 Theoretical Literature Review on Inflation and Stock Returns

The Fisher hypothesis suggests that there is a positive relationship between interest rates and inflation. (Berument & Jelassi, 2002) Fisher (1930) argues that nominal interest rate is entirely a sign of the existing information in relation to the likely future values of the rate of inflation. This hypothesis has come to be known as ‘‘the Fisher effect’’ in the economic literature; it states that expected nominal rates of interest on financial assets should move one-to-one with expected inflation. Choudhry (2001) Fisher hypothesis, in its strict sense, predicts a positive homogeneous relationship of degree one between stock return and inflation. (Luintel & Paudyal, 2008)

The proxy-hypothesis was introduced by Fama (1981) to explain the predominance of negative stock return-inflation trend. The main principle on which Fama's version of the proxy-effect hypothesis is based on is the observed negative relationship between inflation and stock returns which appears to be spurious since this relationship is a result of the positive relationship that exist between stock returns and expected economic activity and an inverse relationship between expected economic activity and inflation. Inflation simply serves as a proxy for expected economic activity in a statistical relationship between stock returns and inflation. (Lee U. , Monday, June 22 1998)

The proxy hypothesis states that the negative relationship between inflation and stock returns is spurious and really only proxies for the positive relationship between stock returns and real variables. Previous testes of the proxy hypothesis have used actual values instead of forecasted values for the real activity variable. (McCarthy, Najand, & Seifert, 1990) did not find a support for the proxy hypothesis using only forecasted variables.

Gonedes (1981) the failure to use indexation means that real income tax rates will vary directly with rates of inflation. This substantive effect of mere bookkeeping methods is frequently predicted even though it is known to have some adverse implications. This is the tax effects of inflation hypothesis.

2.3 Empirical Literature Review on Inflation and Stock Returns

The empirical literature on the impact of inflation on stock returns records major contribution by different scholars over the years. But the empirical evidence provided by most of these studies has been mixed, and a consensus has not yet emerged. While studies like Pierrel and Kwok (1992), Geske and Roll (1983), Floros (2002), Ugur (2005), Yeh and Chi (2009), Pesaran et al (2001), Den Haan (2000), Crosby (2001), Syros (2001), Roohi and Khalid (2002) among others have found a negative relationship between inflation and stock returns; Boudoukh and Richardson (1993), Graham (1996), Choudhry (2001), Patra and Posshakwale (2006) and Lee et al (2000) among others reported positive relationship between these variables.

Concerning the review of the approaches of modeling the effect of inflation on stock returns, Pierrel and Kwoks (1992) estimates and tests the alternative versions of hypothesis that explain the relationship between these two variables. The study employs distributed lags in order to empirically arrive at a dynamic structure of inflation. Pierrel and Kwoks concluded that this dynamic structure conform to Fama (1981), Benderly and Zwick (1985), and Geske et al (1983) hypothesis that suggest a negative relationship between inflation and return on stocks.

Yeh and Chi (2009) tested the validity of the various Hypotheses that explain this relationship. The empirical result of this study on 12 OECD countries shows that these countries exhibit a short-run negatively significant co-movement between stock returns and inflation. Moreover, countries like Australia, France, Ireland and Netherland do not display a long-run relationship between the two variables in equilibrium. This result is consistent with the hypotheses of Fama (1981), Modigliani et al (1979) and Feldstein (1980) which suggested that an increase in inflation reduces real returns on stock. This result is also in line with Caporale and Jung (1997) and Rapach (2002). They argue respectively that there exist a negative significant effect of inflation on real stock returns after controlling for output shock and that inflationary trends do not erode returns on stocks.

The Fisher’s Hypothesis was tested by Spyros (2002). His results reflect a contrary view that returns on stocks hedges inflation. This study shows that there is negative but not statistically significant relationship between inflation and stock returns in Greece from 1990 to 2000. In this same vein, Floros (2002) carried the same study on Greece economy and concluded that inflation and stocks in Greece should be treated as independent variables because the result of the various test conducted show that there is no relationship between inflation and stock returns in Greece. Crosby (2001) investigates the relationship between inflation and stock returns in Australia from 1875 to 1996 and found out that the Australian economy does not experience permanent changes in inflation or stock returns. The result shows that there exist short-run negative relationships between these two variables that depend on the period of time that is considered.

On the contrary, Lee et al (2000) examine the impact of German hyperinflation in the 1920s on stock returns. This result of this study show that the hyperinflation in Germany in early 1920s cointegrates with stock returns. The fundamental relationship between stocks returns and both realized and expected inflation is highly positive. They concluded that common stocks appear to be a hedge against inflation during this period. Choudhry (2001) in his study on the impact of inflation on stock returns in some selected Latin and Central American countries (Argentina, Chile, Mexico and Venezuela) from 1981-1996, reveal that there is one- to-one relationship between the current rate of nominal return and inflation for Argentina and Chile. Their result also reveals that the lag values of inflation affect stock returns and this result infer that stocks act as a hedge against inflation.

Patra and poshakwale (2006) conducted a study on the impact of economic variables on market returns in Greece from 1990 to 1999. Empirical results show that some macroeconomic variable like money supply, inflation, volume of trade and exchange have both short-run and long-run relationship with stock price in equilibrium in Greece while there was no short-run or long run relationship noticed between exchange rate and stock prices.

Ugur (2005) in a study on the effect of inflation on return on stocks in turkey from 1986 to 2000 reveal that expected inflation and real returns are not correlated. The results suggest there is a negative relationship between inflation and stock returns which may be caused by the negative impact of unexpected inflation on stock returns. This results did not contradict Fisherian hypothesis because of the non correlation of inflation and real returns but the results is in line with the proxy hypothesis since a negative significant relationship exist between the two variables. Aperigis and Eleftheriou (2002) results also concurred that there is negative link between inflation and stock returns in Greece than in interest rate and stock returns. Similar study like Adrangi et al (1999) and sellin (2001) also support the proxy hypothesis. Khil and Lee (2000) in their study on ten pacific-rim countries and the US that all the countries except Malaysia reveal negative relationship between inflation and stock returns.

The tax-effects Hypothesis which asserts that there is negative relationship between inflation and stock returns was tested by Geske and Roll (1983). Empirical result from the reveal that random negative or positive real shock affects stock returns which in turn, signal higher or lower unemployment and lower or higher corporate earnings. This has effect on the personal and corporate tax revenue leading to increase or decrease in the treasury through borrowing from the public. The economy paid for this debt by expanding or contracting money growth and this would lead to higher or lower inflation. They concluded that random shocks on stock returns are both fiscal and monetary in nature in the U.S.A.

Roohi and Khalid (2002) considered the Efficient Market Hypothesis and Rational Expectation Theory to investigate the effect of inflation on stock returns. Empirical results of the study suggest that the relationship between real stock returns, unexpected inflation and unexpected growth are negatively significant. They concluded that the control of real output growth makes the negative relationship between these two variables to disappear over time.

2.4 Methodological Literature Review on Inflation and Stocks Returns

The empirical relation between inflation and stock returns has been investigated through various approaches since the 1970s. Spyros (2001), adopted Vector-Auto regressive (VAR) model and the cointegration test to confirm if there was any relationship between inflation and stock returns in Greece. Pierrel and Kwok (1992) investigated the relationship between stock returns and inflation in the United State between 1962-1992 using Vector- Autoregressive (VAREC) model, and Granger Causality, Crosby (2001), used Vector-Autoregressive (VAR) model, Ordinary Least Square (OLS) and correlation analysis to examine the relationship between inflation and stock returns in Australia from 1875-1996.

Floros (2002), investigated the relationship between stock returns and inflation in Greece from 1988-2002 by considering both the lag and lead periods of inflation and stock returns using Ordinary Least Square (OLS), Johansen Cointegration Test and Pairwise Granger Causality Test. In this same vein, Ugur (2005) used the Ordinary Least Square (OLS) and Standard Granger Causality to examine the relationship between inflation, stock returns and real activity in Turkey.

Choudhry (2001), estimate the impact of inflation on stock returns in some selected Latin and Central American countries using the Auto-Regressive Integrated Moving Average (ARIMA), unit root test and spectral regression model. Lee et al (2000); and Geske and Roll (1983), also used ARIMA, OLS and unit root test to investigate the effect of German hyperinflation and stock returns, and the impact of inflation on stocks returns in the USA respectively.

Patra and Poshakwale (2006) on the other hand, used the Error Correction Model (ECM), Johansen Cointegration Test and Pairwise Granger Causality Test to show if economic variables such as money supply interest rate, exchange rate, volume of trade and stock prices have impact on stock returns.

Yeh and Chi (2009) in their study on 12 OECD countries measures correlation at different forecast horizon by using Autoregressive Distributed Lag (ARDL) bound test, unit root test and confidence interval method to investigate the inflation illusion hypothesis that suggest that there is negative relationship between inflation and stock returns. Pesaran et al (2001) and Den Haan (2000) also employ the same technique and arrive at the same result.

This study examines the relationship between inflation and stock returns in Nigeria. Furthermore a test is carried out to see if there’s a cointegration and causality within these variables. Methods used in this study are explained in chapter three. This study fundamentally aims to analyses the above relationship for a period of 1st of January 1997-31st of December 2006 .monthly values of the Nigerian Stock Exchange (NSE) and Nigerian Consumers Price Index (CPI). CPI was collected from the Central Bank of Nigerian Statistical bulletin (2006), while (ASI) All Share Index was collected from Nigerian Stock Exchange data bank.

The reviews of literature above reveal that there are basically four major hypotheses discussing the relationship between inflation and stock returns. These theories are Fisherian hypothesis, proxy hypothesis, tax-effect hypothesis and inflation illusion hypothesis. Considering the level of price stability in Nigeria over the period of our study, the study seeks to adopt Fisherian hypothesis which suggest that stock hedges inflation. This is based on the fact that literature suggests that the price of stock is a major determinant of stock returns which is affected positively by expected or unexpected inflation (consumer price index).

CHAPTER THREE

MODEL SPECIFICATION AND METHODOLOGY

3.1 Introduction

This chapter covers the theoretical framework, specification of the models utilized in the study as well as the methodologies that will be adopted. Accordingly, the estimation procedures, and data requirements; types and sources of data are also discussed in this section.

3.2 Theoretical Framework

The reviews of literature in chapter two reveal that there are basically four major hypotheses discussing the relationship between inflation and stock returns. These theories are;

1. Fisherian hypothesis

2. Proxy hypothesis,

3. Tax-effect hypothesis and;

4. Inflation illusion hypothesis.

The Fisherian hypothesis is thus specified;

Where is the real returns, is the actual inflation which is the combination of the unexpected and expected inflation. While is the error term that is distributed randomly and normally with zero mean and constant variance. This sign of determine if the specification is in line with the fisherian hypothesis. Thus; a significant and positive sign suggest that stock hedges inflation while a negative sign suggest contrary.

3.3 Model specification

Based on the outcome of our theoretical framework which attempts to explain the relationship between real stock returns and inflation, we specify the model for estimation. Stock return represented by all share indexes (ASI) is the dependent variable while the explanatory variables are, one-period lagged inflation represented by consumer indexes (CPI) and one-period lagged stock returns (ASI). This is based on the common belief that stock returns (ASI) takes some time to react to inflationary changes (ΔCPI) and changes in all share indexes (ΔASI). In this study, it is assumed that stock returns depend on a set of variables denoted as:

Therefore, our empirical specification is stated as:

1

3.4 Methodology and Estimation Procedures

This study makes use of Augmented Dickey Fuller (ADF) unit root test to check for the stationarity of the series used in this study, Engle and Johansen cointegration tests is used to confirm if the series have long run relationship while causal long run relationship is determine using an Error correction Model (ECM) which will reveal both the short run and long run relationship between inflation (LOGCPI) and stock returns (LOGASI).

3.4.1 Unit Root Test

Assume we have the following AR (1) process: (1)

and is a white noise error term. We can manipulate the above expression by subtracting from both sides;

Thus: (2)

In practice, instead of estimating equation 1, we estimate equation 2 and test the hypothesis that =0. If =0 then that is we have unit root meaning the time series is non-stationary ( for unit root is non-stationary). Thus we can take the first difference of and regress on to see if () is zero or not in order to confirm if the series are stationary or not. Under the null, the estimation for δ is not distributed T-student, so the Dickey Fuller test is required. We use the Augmented Dickey Fuller (ADF) table to correct for possibility of the error term () been auto correlated. The ADF test is specified in the equation below:

3

Where is a white noise Error Term.

3.4.2 Co integration Tests

Trended data can be regarded as potentially a major problem for empirical econometrics. Trends may give rise to spurious regression and uninterpretable t- statistics. The stack reality is that in economics most time series are subject to some type of trend while differencing in series until it becomes stationary is one major solution. This has been shown that differencing can lead to loss of long run properties of a series. Based on this the combination of series that are difference once I(1) will give us a model that is stationary I(0). In achieving this aim this study consider two different co integration tests which are; Engle and Granger co integration test and Johansen co integration test. According to Engle and Granger (1987), a time series and are said to be co integrated of order db where d ≥ b ≥ 0 written as: CI (db) if:

Both series are integrated of order d

There exists a linear combination of these variables say; which is integrated of order d-b. The vector and is called a co integrating vector.

The Engle and Granger co integration test involve two steps; the first step is conducting an OLS regression on the variables in the model specification. The second step is to conduct an ADF test on the residual from the regression if the residual is stationary, then the series are said to be co integrated.

The Johansen co integration test on the other hand involves the use of a VAR model and the different maximum likelihood ratios are used to determine the co integrating vectors. These tests are; trace test and maximum eigen value test. Different information criteria such as Akaike Information Criterion, Schwarz information criteria (SIC), Hannan-Quinn Information Criterion, Final Prediction Error and Sequential Modified test Statistic are used in determining the lag length.

3.4.3 Error Correction Model

Co integration analysis provides a test for spurious correlation. Finding co integration between apparently correlated I(1) series validate the regression but failure to find co integration is an indication that spurious correlation maybe present thus invalidating the inferences drawn from such correlation. Co integration analysis also helps in formulating the process of dynamic adjustment. However time series data lose their long run properties when they are differenced; allowing only for conclusions on the short run determinations. Therefore there is a need to construct a model that would combine both the short run and long run properties of the variables in the model. As suggested by Engle-Granger representation theorem that if two series are co integrated then they will be efficiently represented by an error correction mechanism. The Error Correction Model is used to capture both the short run and long run properties of the series. The method involves developing a model from it generalized form (over parameterized) to a specific form (parsimonious). In addition if the series are co integrated these dynamic specifications will encompass any other partial adjustment model. The error correction of the Auto regressive distributed lag (ADL) takes the form: where the long run properties are derived from the proportionality between and. The above specification relates the short run change in the dependent variable to the short run change in the explanatory variable.this is called the impact effect () but ties the change to the long run impact through a feed-back mechanism.

3.5 Data

The study will utilize monthly time series data from 1997–2006. Data for the variables will be sourced from Central Bank of Nigeria Statistical Bulletin (2006) and the Nigerian Stock Exchange Annual Reports (2006). The variables of interest in this study are all in logs. These variables are; consumer price indexes (CPI) as inflation series and all share indexes (ASI) as stock returns.

CHAPTER FOUR

SUMMARY OF EMPIRICAL RESULTS

The summary of the statistics used in this empirical study is presented in the appendix. As can be observed from the Table, (see pagexx) the mean value of stock returns is 9.359606 while inflation is 8.442205. It is also observed that both LOGCPI and LOGASI are positively skewed. The kurtosis value is positively low and Jarque-Bera (J-B) statistic test value is relatively high. These suggest that the two series are skewed to the right.

Figure1below depicts the graphical illustrations of the data that were used in this empirical analysis. The figure reveals that stock return witnessed significant increase within the period of this study.

Figure 1: Graphical illustration of statistics used in the analysis

Table 1: Stationarity Test Result

Variables

Levels

First Differences

ADF 1

ADF 2

ADF 1

ADF 2

LOGASI

0.712327

-2.440634

-9.385773*

-9.586827*

LOGCPI

0.244088

-2.680445

-9.152876*

-9.113796*

SOURCE: Author’s Computation

NOTE: The Augmented Dicky Fuller test ort the null Hypothesis of the presence of Unit root in LOGASI and LOGCPI. ADF 1 includes a constant; ADF 2 includes a constant and a trend while ADF 3 includes none in the test regression as exogenous. Akaike Information Criterion was used to select lags automatically. * denotes significance at all levels (1%, 5% and 10%).

The results from the unit root test are introduced in table 1. the above results, shows that the data are not stationary in level, since the critical values are high when compare to the ADF statistics and probability value is very high indicating that it is not statistically significant at all significance levels in ADF 1 and ADF 2 Furthermore, the variables became integrated of order one at first difference in ADF1 and ADF2 considering the low probability value and critical values that are significant at 1%, 5% and 10% when compare to the ADF test statistics.

The result in table 1 show that LOGASI and LOGCPI are both nonstationary series at level are both I (1) series. This implies the above Augmented Dickey Fuller (ADF) tests suggest that LOGASI and LOGCPI are of the same order of integration.

next, we test for co integration to ascertain if the two series have a long run relationship since the linear combination of I(1) series will give an I(0) series which imply stationarity. The Engle and Granger co integration approach is adopted for this task. This approach involves two steps; the first step involves the estimation of a static OLS regression which captures any possible long-run relationship between LOGASI and LOGCPI. The OLS regression model is specified as follows:

(1)

Secondly an ADF test is conducted test on the residuals of the OLS regression specified in equation one above. For co integration to exist, the residuals () must be I (0) meaning, the residuals term must be integrated to the order of zero. If the null hypothesis (has unit root) is rejected then and are co integrated. The OLS regression result and ADF test on the residuals are presented in table 2 and table 3 respectively.

Table 2: OLS result

Dependent Variable: ASI

Method: Least Squares

Variable

Coefficient

Std. Error

t- Statistic

Prob

A

-0.418581

0.166356

-2.14971

0.0133

0.542636

0.258431

2.099735

0.0380

-0.424224

0.257403

-1.648089

0.1021

1.059213

0.092307

11.47485

0.0010

-0.120618

0.090882

-1.327150

0.1871

= 0.9921

Adjusted = 0.99178

Durbin Watson: 2.04929

Note: model:

Table 3: ADF Test on Residual ()

Lag Length: 0 (Automatic based on AIC, MAXLAG=1)

t-Statistic

Prob.*

Augmented Dickey-Fuller test statistic

-11.59144

0.0000

Test critical values:

1% level

-2.584877

5% level

-1.943587

10% level

-1.614912

*MacKinnon (1996) one-sided p-values.

Augmented Dickey-Fuller Test Equation

Dependent Variable: D(RESIDUAL)

Note: the lag length was determine automatically based on AIC using EViews statistical Package

In the above test, constant or trend are not included because the test is conducted on the residuals of the OLS regression conducted in equation one above. The result suggests that the residuals stationary which implies that stock returns and inflation are co- integrated. Therefore we can conclude that there is a long run relationship between stock returns (LOGASI) and inflation (LOGCPI).

The Engel co-integration results above reveal that there is long run relationship between inflation and stock returns therefore we can determine the causal long run relationship using the Error Correction Model (ECM). The Hendry’s modeling strategy of selecting the most appropriate model by going from general to specific is adopted .we use for this purpose information criterion such as Akaike (AIC)

Model Specification:

(2)

The result of the regression conducted on the over parameterized model is presented in table 4 below.

Table 4: Regression result of the Over Parameterized Model

Dependent Variable:

Variable

Estimates

‘t’ Statistic

Constant

0.0006

0.10087

-0.0794

-2.9266*

0.3131

1.1815

0.3203

1.2232

0.1829

0.7046

0.0869

0.9469

0.1266

1.3634

Note: * indicate 1% significant level

From the above results, it is observed that only the lag value of the residual is statistically significant. The model arrived at, is regarded as the more parsimonious model that encompasses both the short run and the long run relationship between stock returns and inflation. Table 5 below, is the presentation of the ECM model.

Model Specification: (3)

Table 5: Error Correction Model

Equation:‘cause’

Dependent Variable:

Variable

Estimates

‘t’ Statistic

Constant

0.00627

1.11380

-0.06111

-2.28680*

0.43796

1.69621**

0.13611

1.50363

*indicate 5% significance level and

** 10% significance level

The above result suggest that there is long run causal relationship between inflation and stock returns. The result reveal that estimated coeffient of the lagged value of the error correction mechanism () is negative and statistically significant. This is in line with the apriori expectation suggested by theory. The result also implies with a significance level of 10% that a change in one period lagged value of inflation () has a positive and statistically significant effect on changes in stock returns (). This means that inflation value of a previous month, has positive influence on the changes noticed in stock returns in the current month. Although, the one period lagged value of stock returns() but it is statistically insignificant.

CHAPTER FIVE

SUMMARY AND CONCLUSION

5.1Summary of Major Findings

Nigeria’s inflation position post advent of oil reflects the instability in price that was witnessed in internal and external sectors of the economy. The structural changes such as oil revenue fluctuations, deregulation of the economy, real income reduction, changes in nominal wages fiscal deficits are major causes of price instability in Nigeria. In analyzing the trend and pattern of stock returns vis-à-vis the performance of government stocks and companies stock in Nigeria, This study reveal that between 1963 and 1990 government stock exceed companies stocks. There was a change in this trend from 1991; trading on stocks of industries and companies increased remarkably thereby making companies stocks’ more attractive and profitable for investors. The increase in market capitalization was noticed in the economy within these periods has no significant effect on gross domestic product and gross fixed capital formation. This situation has negative impact on the return on investment in these periods.

In summary, the Augmented Dickey Fuller (ADF) test shows that inflation (CPI) and stock returns (ASI) are both I(1) series and the Engel and Granger co integration test which is the linear combination of the I(1) series indicates that inflation and stock returns have a long-run steady-state relationship in Nigeria. The Error Correction model indicates that inflation (CPI) has a causal long run relationship with stock returns (ASI). The one period lagged value of inflation () causes the short run changes noticed in the level of stock returns within the period of this study. The empirical result also reveal that there is a positive relationship between inflation and stock returns which invariably means that inflation (CPI) and stock returns (ASI) move in the same direction which is evident in the graphical illustration.

These findings explain why stock returns in Nigeria have witnessed fluctuations. It also revealed that overtime, inflation has been noticed as one of the major factor that determines the fluctuation in returns on investment in Nigeria.

5.2 Conclusion

The relationship between inflation (CPI) and stock returns (ASI) has been implied in the model of stock return determination and return on investment literature. However, this relationship has remained largely unexplored. Inflation and what happens to the overall return on stocks is an important indicator that must be considered by any investor when investing on stocks in Nigeria. The study Therefore concludes that inflation is a vital macroeconomic variable that influence the flow of investment and determines the direction and changes noticed in return on stocks in Nigeria overtime.

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