However finance theory assumes idealistic models for the stock markets and formulates the investor utility functions and expectations accordingly. These models are based on perfect competition and passage of information in an unfettered manner. As Wikipedia (2007) seems to point out, "In economics and financial theory, analysts use random walk techniques to model behavior of asset prices, in particular share prices on stock markets, currency exchange rates and commodity prices. This practice has its basis in the presumption that investors act rationally and without bias, and that at any moment they estimate the value of an asset based on future expectations. Under these conditions, all existing information affects the price, which changes only when new information comes out. By definition, new information appears randomly and influences the asset price randomly.
Empirical studies have demonstrated that prices do not completely follow random walk. Low serial correlations (around 0.05) exist in the short term. and slightly stronger correlations over the longer term. Their sign and the strength depend on a variety of factors, but transaction costs and bid-ask spreads generally make it impossible to earn excess returns. Researchers have found that some of the biggest prices deviations from random walk result from seasonal and temporal patterns. In particular, returns in January significantly exceed those in other months (January effect) and on Mondays stock prices go down more than on any other day. Observers have noted these effects in many different markets for more than half a century, but without succeeding in giving a completely satisfactory explanation for their persistence. Technical analysis uses most of the anomalies to extract information on future price movements from historical data. But some economists, for example Eugene Fama, argue that most of these patterns occur accidentally, rather than as a result of irrational or inefficient behavior of investors: the huge amount of data available to researchers for analysis allegedly causes the fluctuations. Another school of thought, behavioral finance, attributes non-randomness to investors’ cognitive and emotional biases".
Taking an apposite viewpoint Leverton () states, "Without market fundamentals being able to predict prices, the investor is forced to learn new ways of investing.. Ratios and trend analysis are important to picking a winning portfolio. Subscribers to the adaptive expectations theory believe investors are
backward looking in deciding on the correct price to pay for a stock". Realized and expected rreturns from the stock markets have been the subject of intense debate since a long period of time .Several theories suggesting various constructs and factors responsible for determining the returns from the stocks have been postulated thus far.It was not until the late 1960s and early 1970s that a fully-developed, empirically-supported theory of share prices’ behavior emerged in the form of the Efficient Markets Hypothesis (EMH).Prior to the development of the EMH , analysts assumed some degree of dependence across successful price changes. Very many efforts were made towards identifying a predictable trading pattern which could be used for chasing profitable deals. From the mid-1950s to the early 1980s, a random walk theory (RWT) of share prices was developed based on the past empirical evidence of randomness in share price movements. RWT