A RANDOM WALK DOWN MAJOR STOCK MARKETS IN THE SUB SAHARAN AFRICA:

AN EMPIRICAL TEST IN THE SOUTH AFRICAN, KENYAN, NIGERIAN AND GHANAIAN CAPITAL MARKETS

George Michael Fudjoe

CONTENTS

Introduction

Objective of the study

theoretical framework and review of literature

Research hypothesis & methodology

References

INTRODUCTION There have been significant development in the sub Saharan

African capital markets since early 1990s 5 stock markets before 1989 ; Currently there are about 19 Establishment of capital markets have been central to domestic financial liberalization

agenda of most African countries

However we cannot be concluded that these capital markets are mature since they are characterized by Few stock trades contributing immensely to market capitalization Inadequate regulatory supervision Informational deficiencies for some stocks Low liquidity

According to Singh(1999) critics have argued that it may not be feasible for all African markets to promote stock markets, given the huge costs and the poor financial structures

Perhaps motivated by the fact that Investors may be unwilling to invest in the stock market where high inflation is

expected Unstable macroeconomic environment, low income levels, Low GDP per capita, etc.

(Garcia and Liu, 1999)

INTRODUCTION CONT’D Why are stock prices in sub Sahara African capital

markets: Less responsive to market information Characterised by low levels of participation and less active as compared

to developed markets

These questions have: Necessitated an enquiry into the efficiency of capital markets in sub

Saharan Africa Promoted the need to assess the significance of roles played by

fundamental and technical analysts

And as a result begged further questions like: Are they relevant Can our markets function indifferently without them Can investors benefit from these analyses and make above normal

profits within this region

OBJECTIVE OF THE STUDY

The main objective of this study is to determine whether there exists randomness in price changes on major stock markets in sub Saharan Africa.

Other objectives this study aims at is to:

Question the ability of investment firms to predict stock prices in sub Saharan African stock markets

Assess the relevance of Investment houses in providing advisory services to active and potential investors

Understand to a degree the irresponsiveness of some stock prices to significant information

THEORETICAL FRAMEWORK AND REVIEW OF LITERATURE

The idea of stock prices following random walks is connected to that of the Efficient Market Hypothesis (EMH) which has been debated since its introduction

The random walk model was first developed by (Bachelier, 1900) where he stated that successive price changes between two periods is independent with mean zero and its variance proportional to the interval between the two time periods.

A market where successive price changes in individual securities are independent is by definition, a random walk market (Fama, 1965)

A random walk is defined by the fact that price changes are independent of each other (Brealey et al, 2005)

A market is said to be efficient if prices ‘fully reflect’ available information (Fama, 1970)

What this means is that prices of a security at any point in time will fully reflect information available and no profit can be made from information based trading (Lo and MacKinley, 1999)

RESEARCH HYPOTHESIS & METHODOLOGY Hypothesis

H0: Stock price movements in sub Saharan stock markets do not follow a random pattern (=0)

H1: Stock price movements in sub Saharan stock markets follow a random pattern (≠0)

Population of the Study The population for this study will be the price of all listed firms on stock

markets in Ghana (GSE), Nigeria (NSE), Kenya (NSE Kenya) & South Africa (JSE).

Sources of data All data will be collected online from www.afx.kayisi.org at fee; Validity of data

will be confirmed from country statistical bulletins, stock exchange websites & http://www.tradingeconomics.com

RESEARCH HYPOTHESIS & METHODOLOGY Data Analysis Technique 

The augmented Dickey-Fuller (ADF) autoregressive model will be used in this study to test for randomness

  The intuition behind the technique is that if a series is stationary, that is, a stochastic

process whose joint probability distribution does not change when shifted in time, consequently, parameters such as the mean and variance, if they are present, also do not change over time and do not follow any trends

It can therefore then be said that the series has a tendency to return to a constant or deterministically trending mean with negligible trace of randomness

This model is preferred to the (DF) which removes all the autocorrelation in the time series and then tests using the same procedure as DF.

Model Specification 

The Dickey-Fuller Model:∆yt = yt-1 + µt; where ∆ is the first difference operator

REFERENCESBrealey, R., Myers, S., & Allen, F. (2008). Principles of corporate finance. Boston: McGraw-Hill/Irwin.

Fama, E. (1965). The Behavior of Stock-Market Prices. The Journal Of Business, 38(1), 34.

Fama, E. (1970). Efficient Capital Markets: A Review of Theory and Empirical Work. The Journal Of Finance, 25(2), 383

Kenny, C., & Moss, T. (1998). Stock markets in Africa: Emerging lions or white elephants?. World Development, 26(5), 829-843.

Lo, A., & MacKinlay, A. A non-random walk down Wall Street.

Singh, A. (1999). Should Africa promote stock market capitalism?. Journal Of International Development, 11(3)

Yartey, C. (2010). The institutional and macroeconomic determinants of stock market development in emerging economies. Applied Financial Economics, 20(21), 1615-1625.