Blog 1

How efficient is the stock market?

Many academics are fascinated by whether the stock market is efficient in pricing shares and other securities, and are attracted by the thought that studying this area may lead them to discover inefficiency. In an efficient market, there is no undervaluing or over valuing of shares and prices rationally reflect available information.

 An ‘efficient’ market is defined as a market where there are large numbers of rational, profit ‘maximisers’ actively competing, with each trying to predict future market values of individual securities, and where important current information is almost freely available to all participants. In an efficient market, competition among the many intelligent participants leads to a situation where, at any point in time, actual prices of individual securities already reflect the effects of information based both on events that have already occurred and on events which, as of now, the market expects to take place in the future. In other words, in an efficient market at any point in time the actual price of a security will be a good estimate of its intrinsic value. (Fama,1970)

An investment theory that states it is impossible to "beat the market" because stock market efficiency causes existing share prices to always incorporate and reflect all relevant information. According to the EMH, stocks always trade at their fair value on stock exchanges, making it impossible for investors to either purchase undervalued stocks or sell stocks for inflated prices.

In terms of efficiency, economists have identified three levels according to the type of information which is reflected in prices. Fama (1970) produced a three level grading system which consists of

Weak-form efficiency: Share prices reflect all information from past price movements, which is viewed as inefficient because future share prices cannot be determined using historical information.  

Semi-Strong form efficiency: Share prices fully reflect all relevant publicly available information, which includes not only past prices, but also earnings and dividend announcements. As this form uses all public information to calculate a stock's current share price, it means that neither fundamental nor technical analysis can be used to achieve superior gains.

Strong-form efficiency: The strongest version of market efficiency. It states all information in a market, whether public or private, is accounted for in a stock price. Insider dealing can occur, when a few privileged individuals are able to trade in shares, as they know more than the normal investor in the market. However, they are unable to make abnormal profits as the market is acknowledged as being inefficient at this level of definition, according to Arnold.

In an article written by John Authers, he says that markets are not always efficient, and more or less everyone agrees with this in the wake of the financial crisis of 2008. He continues to describe how even though technology is rapidly improving to make markets faster, markets are now more inefficient that they used to be. The most popular answer to blame is the greed and fear of human nature. According to an article written by John Cassidy, part of the problem is how financial economists define efficiency. In most areas of economics, efficiency is defined in terms of how well markets allocate resources. If a given market allocates them in a way that leaves it impossible to increase the welfare of one person without lowering the welfare of at least one other person, the market is said to be “Pareto efficient.” One of the big achievements of twentieth-century economics was in showing how, under certain highly restrictive conditions, a free-market economy can produce a Pareto-efficient outcome.

In the 1950’s, Maurice Kendall analysed a paper for regular price cycles, but was unable to identify any. He found that the prices of shares moved in a random fashion with no patterns or trends. This opposed the belief that analysis could be used to beat the market, as prices followed a random walk. There have been tests to demonstrate that random walk does exist, as well as tests to prove that it does not. For example, a simple test carried out by Andrew W. Lo and A. Craig Mackinlay, from the University of Pennsylvania, strongly argue that stock market prices do not follow random walks. They mention that few studies have been able to reject the random walk hypothesis, for example Keim and Stambaugh (1986) find statistically significant predictability in stock prices by using forecasts based on certain predetermined variables. In addition, Fama and French (1987) show that holding long period returns are significantly negatively serially correlated, implying that 25%-40% variation of longer horizon returns is predictable from past returns. Arguments and evidence to disprove whichever hypothesis has been carried out for many, many years and academics are likely to be researching this topic for many more.