Abstract
The Random Walk is considered to be a tool trying to explain the characteristic of movement of prices in the financial markets. It can also be seen in the form of a trial to demonstrate the non-predictability of future changes in the financial markets through reliance on the characteristics identified based on past price changes. In this paper used is the variance-ratio test initiated by Lo and MacKinlay to test the Random Walk Hypothesis for a more recent data of eleven Stock Indexes, seen as main indexes of the current market.
Highlights
As any investor would wish to be able to predict the movement direction of some asset price, the Random Walk Hypothesis argues it not to be a realistic option
The efficient market hypothesis (EMH) states that all the share prices are a reflection of its relevant information, whereby the stocks trade at the price they are worth
These results show that indexes of DAX, IBEX35, HANG SENG, BSE30, and Nikkei do not reject the hypothesis of a random walk with a significance level of 0.05, as the values for each of them falls within the symmetric range of the standard normal distribution, between -1.96 and 1.96, covering the confidence level of 95%
Summary
As any investor would wish to be able to predict the movement direction of some asset price, the Random Walk Hypothesis argues it not to be a realistic option. Just as the name itself suggests, the assumption of the Random Walk Hypothesis (RWH) is that the prices experience change (walk) in an unpredictable direction and measure. Efficient Market defines a market where all the relevant information that impacts the price of a financial instrument is available to everyone at no additional cost. The efficient market hypothesis (EMH) states that all the share prices are a reflection of its relevant information, whereby the stocks trade at the price they are worth. The weak form efficiency, known as a random walk, corresponds to the situation where the data of past changes in price and the volume of trade have no impact on the current stock prices
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More From: Periodicals of Engineering and Natural Sciences (PEN)
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