The objective of this project is to investigate whether prices in stock markets follow a weak form efficient process.

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TABLE OF CONTENTS

  1. Introduction

The concept of ‘efficient’ stock market has been hotly debated ever since Eugene Fama first introduced it around some thirty years ago. Under the weak form of market efficiency, the price of a security reflects all the available information about the economy, the market and the specific security, and that prices adjust immediately to new information. For a long time the conformation of random walk is considered to be a sufficient condition for market efficiency. However, rejection of random walk model does not necessarily imply the inefficiency of stock-price formation.

Random walk is the path of a variable over time that exhibits no predictable patterns at all. If a price, p, moves in a random walk, the value of p in any period will be equal to the value of p in the period before, plus or minus some random variable. The random walk hypothesis states that the present market price is the best indicator of the future market prices with an error term that is stochastic in nature. Hence the next time period price is anybody’s guess. In an efficient market it is not possible to make profit based on the past information hence the prediction of the future price conditional on the past prices on an average should be zero. The more efficient a market is the more random and unpredictable the market returns would be. In the most efficient market the future prices will be totally random and the prices formation can be assumed to be a stochastic process with mean in price change equal to zero.

The objective of this project is to investigate whether prices in stock markets follow a weak form efficient process. The presence or absence of such a process in the stock markets is evaluated using stock market indices and returns. The study is made comprehensive by including three stock market indices and another three indices of individual stocks belonging to the respective stock markets under examination. The observations are tested using the methodologies which are common for this area of study.

  1. Data and Methodology

There are various indices available that are widely used as the indicator of the performance of the stock markets in the world. These indices are constructed based on different methods and hence are expected to behave differently. Three different stock market indices and three individual company indices each from their respective stock markets are used in this paper. The market indices are:

  1. Dow-Jones Industrial Average Index (United States of America)
  2. TOPIX (Japan)
  3. CAC40 (France)

The company stock indices include:

  1. General Electric (United States of America)
  2. Honda Motors (Japan)
  3. L’Oreal (France)

The above mentioned market and company indices seem to be some natural choices for including in this report, as they are relatively popular and widely used by market players for benchmarking. Considering their substantial sizes and relatively large shares in local and world equity markets, one can exhibit very large volumes, high liquidity, comprehensive measures of stock price changes and instantaneous information distribution. TOPIX. For instance, includes all first section listed shares in the Tokyo Stock Exchange (TSE) which comprises some 1500 companies of all kind from all over Japan and the world. The index   is computed and published every 60 seconds via TSE's Market Information System. It is reported to securities companies across Japan and is available worldwide through computerized information networks. Moreover, existence of available data on the indices for a large period of time is an added advantage for the study. The study spans more than 12 years, starting from 31 December 1989 till 31 December 2001 for monthly data; and begins from 29 December 1989, extending till 31 December 2001 for daily data. All the factors mentioned provide a relatively ideal ‘condition’ for testing weak form efficiency.

Of the three market indices, only the DJIA runs as a simple price average mechanism (in fancy definition is a price weighted index). The rest two indices are based on a more popular value weighted procedure.

To give a rough idea how the indices are calculated. Each stock in the Dow Jones Industrial Average represents 1/30th of the overall average. The way the average is calculated is simply by adding up each stock price and divides by 30 (or the amount of stocks that were in the index at that time). Because of stock splits, they had to adjust the divisor. Today, with respect to the Industrial Average, the way to figure out how a one point move in any one stock affects the amount of points up or down the index moves, divide one by the current divisor. For example, if Philip Morris (MO) is down 4 points, divide 4 by 0.33098002 (the current divisor) = 12.085. Therefore, if the Dow Jones Industrials were down 20 points today, and Philip Morris was down 4 points, 12.085 of the 20 point decline would be attributed to Philip Morris.

For the value weighted indices (also known as market weighted indices), the market value of a stock is computed as the closing price times the number of shares outstanding. This expression is often called the stock’s capitalisation or ‘cap’. As a result, the value-weighted indices are biased toward the companies with the highest stock market value: a move in Honda will affect the TOPIX more than a move in Japan Wind Development.

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Both daily and monthly prices are collected for this report, and based on the prices, return can be calculated as the logarithmic difference between two consecutive prices in a series. With the index levels and returns handy, various statistics can be carried out.

  1. Jarque-Bera Statistics for Normality

The test for normality is carried out with the Jarque-Bera statistics provided by the EViews package. This is a test statistic for testing whether the series is normally distributed using skewness and kurtosis based on least squares residuals. The test statistic measures the difference of the skewness and kurtosis of the series ...

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