Market Efficiency Theory

Market Efficiency Theory
Market efficiency was formulated by Eugene Fama in 1970, labeled as efficient market hypothesis. His theory suggests that stock and market value are based on publicly available information. Investors invest with the goal that their investment will generate a positive return on their investment. An efficient capital market is when a stock price reflects publicly available information that may affect the stocks value, which could benefit investors. Efficient markets generate random patterns that cannot be predicted, and an investor cannot factually predict a stock value with secretive information.

Less Efficient U.S. Markets
Markets are much more inefficient than they used to be, and unreliable information could cause investors to receive inefficient values. If markets are unreliable, the value could potential plummet and non-informed investors may not be interested in purchasing new stock. Furthermore, An inefficient market would likely be placing a market value above or below its true value. An inefficient market creates unfair advantages for certain investors who would not otherwise have access to the company’s information. Markets become less efficient often due to greed, economic involvement, negligence, and lack of communication.

Markets in Other Countries
Many studies have found that market prices are difficult to predict. Compared to the United States, other countries also have problems with market inefficiency. Market efficiency asserts that there is no pattern or trends that can be used to predict future value. In the Indian capital market for instance, market inefficiency exist that contradict the efficient market hypothesis. A study, which examined a calendar anomaly within the stock market; found that stocks often held until after the New Year present a higher return rate, and that Monday is considered the worst day of the week to invest. While this isn’t considered inside information, it does create a predictable trend that creates a level of efficiency to use in predicting market trends and potential.

Finding efficiency within the stock market may seem fairly simple with the use of technology and cheap software tools that can find patterns within stock prices. However, the reality is that there is no way in determining the direction of a stock by using computer technology or human assumptions. In addition, if exploits did exist, they would be found and corrected to prevent future defrauding.

With the efficiency market hypothesis, the securities will always reflect the available public information. No system, tool, calculation, or individual investor has access to secret information that would help them generate a rate of return above others. Consequently, investors should always expect to receive a fair value for their securities.

To determine the direction of a stock, investors must be skilled at analyzing data, predicting stocks, and have the ability to comprehend statistics and understand the stocks industries. To achieve this, it takes an investor that is passionate and has the time to evaluate the market.

In addition to rationality, independent deviations from rationality, and arbitrage, t he efficiency market hypothesis makes the assumption that there are three levels of market efficiency’s. The three levels assume that the value of an investment should reflect all available information. Prices should change based only on publicly unexpected information. The hypothesis is considered a model based on how markets tend to work and not how they should work. The three levels of market efficiency include strong, semi-strong, and weak (Maguire, 2010; Ross, Westerfield, & Jaffe, 2013). The weak level of efficiency does not base it results on reliable data such as earnings, forecast, or company announcements. However, they are often random and based on mathematical assumptions relating to historical data. A market is considered semi-strong if it can be predicted by using publicly available information. Information that helps predict a market using a semi-strong efficiency level includes information regarding accounting statements, and historical data. The strong efficiency level uses all publicly and privately available information to determine a stocks value.

Insider trading behavior is affected by expected trading profits from private information, and potential litigation risk. Managers tend to avoid trading before company disclosures so that they may avoid litigation risk. To reduce the probability of litigation, managers provide higher quality disclosures before insider trading. Furthermore, to avoid litigation, insiders often avoid profitable trades before earnings announcements, but will trade after the announcement in an attempt to profit from their future earnings based on the announcement.