# Econometrics of Random Walk Hypothesis

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Econometrics of Random Walk Hypothesis

ABSTRACT

The random walk hypothesis is a key instrument used in the analysis of forecasting in the economic and financial market. It is used primarily in the forecasting of the prices of stocks. This is useful to determine and forecast the prices of stocks given previous stock prices. This paper discusses the basis of the hypothesis, the two types of random walk hypothesis, its framework, methodologies and the analysis of its repercussions.

INTRODUCTION

The random walk hypothesis states that stock price changes have the same distribution and are independent of one another, so the past movement or trend of a stock price or of the market as a whole cannot be used to predict its future price or any possible future trends. The concept originated in the late 1800s from Jules Regnault, a French broker, and Louis Bachelier, a French mathematician, whose Ph.D. dissertation titled "The Theory of Speculation". The same ideas were later developed and studied further by Paul Cootner, an MIT Sloan School of Management professor, in his 1964 book The Random Character of Stock Market Prices. The term was popularized by the 1973 book, A Random Walk Down Wall Street, by Burton Malkiel, a professor of economics at Princeton University, and was used earlier in Eugene Fama's 1965 article "Random Walks In Stock Market Prices”. The theory that stock prices move randomly was earlier proposed by Maurice Kendall in his 1953 paper, “The Analytics of Economic Time Series, Part 1: Prices”.

To further the understanding of the random walk hypothesis, the discussion of the two techniques used in the prediction of stock prices. These two are (1) chartist or technical techniques and (2) the theory of fundamental or intrinsic value analysis. The assumption with chartist or technical techniques is that history tends to repeat itself. Thus, previous data

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