Stock Market Prediction

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Category: Stock Market Report

Stock market prediction is the act of trying to determine the future value of a company stock or other financial instrument traded on a financial exchange. The successful prediction of a stock's future price could yield significant profit. Some believe that stock price movements are governed by the random walk hypothesis and thus are unpredictable. Others disagree and those with this viewpoint possess a myriad of methods and technologies which purportedly allow them to gain future price information.

When applied to a particular financial instrument, the random walk hypothesis states that the price of this instrument is governed by a random walk and hence is unpredictable. If the random walk hypothesis is false then there will exist some (potentially non-linear) correlation between the instrument price and some other indicator(s) such as trading volume or the previous day's instrument closing price. If this correlation can be determined then a potential profit can beamed. Prediction methodologies fall into three broad categories which can (and often do) overlap. They are fundamental analysis, technical analysis (charting) and technological methods.

Fundamental Analysts are concerned with the company that underlies the stock itself. They evaluate a company's past performance as well as the credibility of its accounts. Many performance ratios are created that aid the fundamental analyst with assessing the validity of a stock, such as the P/E ratio. Warren Buffett is perhaps the most famous of all Fundamental Analysts. Technical analysts or chartists are not concerned with any of the company's fundamentals. They seek to determine the future price of a stock based solely on the (potential) trends of the past price (a form of time series analysis). Numerous patterns are employed such as the head and shoulders or cup and saucer. Alongside the patterns, statistical techniques are utilized such as the exponential moving average (EMA).

With the advent of the digital computer, stock market prediction has since moved into the technological realm. The most prominent technique involves the use of artificial neural networks (ANNs) and Genetic Algorithms. ANNs can be thought of as mathematical function approximates. Their value in stock market prediction is that if a (potentially non-linear) relationship exists then it is possible that it could be found with enough indicators, the correct network structure and a large enough dataset. The most common form of ANN in use for stock market prediction is the feed forward network utilizing the backward propagation of errors algorithm to update the network weights. These networks are commonly referred to as Back propagation networks. Since NNs require training and have a large parameter space, it is useful to modify the network structure for optimal predictive ability. Recently this has involved pairing NNs with genetic algorithms, a method of finding optima in multi-dimension parameter spaces utilizing the biological concepts of evolution and natural selection. Moreover, some researchers have tried to extract meaningful indicators from the news flash and discussion rooms about a certain stock using Data Mining techniques. But people can have different opinion about the same stock at the same time.