Random Behaviour in the Stockmarket

Over the years there have been many research projects which aimed to find out if market action was random or whether there was proof that it could be predicted on a regular basis. If you are trading the stockmarket, there would be no point in playing the game if it was purely random, and various important papers have shown a distinct repetition of patterns both in price and time cycles, which effectively confirm that market action is not random.

Charts often exhibit similar pattern behaviour in indices, forex, treasury bonds and commodities, aswell as share prices. Nevertheless, there are times when action does appear haphazard, and one explanation for this is what is called the ‘random walk theory’.

Random walks and efficient markets

There have been three main works of note which attempted to ‘explain’ random action. In 1973 Burton Malkiel wrote "A Random Walk Down Wall Street", which has become one of the most widely known investment works. The book expounded on his stock market theory in which he stated that the past movement or direction of the price of a stock or overall market could not be used to predict its future movement.

This was an extension of work carried out twenty years before, when Maurice Kendall put forward a theory that stock price fluctuations are independent of each other and have the same probability distribution, but that over a period of time, prices maintained an upward trend.

It all comes down to how ‘efficient’ the market is viewed to be, and “The Efficient Market Hypothesis” evolved in the 1960s from a Ph.D. dissertation by Eugene Fama. EMH stated that at any given time, security prices fully reflected all available information, which is a fairly radical statement.

His view was that in an active market that included many well informed and intelligent investors, securities would be appropriately priced. They would reflect all available information, and if the market was efficient, no information or analysis could be expected to result in outperformance of an appropriate benchmark. In the market, there were large numbers of competing players, with each trying to predict future market values of individual securities, and where important current information was almost freely available to all participants.

This would lead to a situation where current prices of individual securities already reflected the effects of information based both on events that have already occurred and on events which were expected to take place in the future.

Trying to dismiss technical and fundamental analysis

EMH was seen to have three forms:

The "Weak" form asserted that all past market prices and data were fully reflected in securities prices. In other words, technical analysis was of no use.

The "Semistrong" form asserted that all publicly available information was fully reflected in securities prices. In other words, fundamental analysis was of no use.

The "Strong" form asserted that all information was fully reflected in securities prices. In other words, even insider information was of no use.

Those three forms effectively dismiss all analysis as futile, whether it be technical or fundamental. Obviously when a trader takes a position, this is based on a view of mispricing in their favour, and in this respect there have been many papers proving that the market is indeed not random. A glance at chart books from the 1970s for instance often shows remarkably similar price action to that seen on current charts, and again similar patterns are often visible to forex and commodity traders.

The other view – the market is not random

A cursory glance at the long term performance of many consistent money managers would indicate that the idea of a purely random market is nonsense. There are many examples of traders who have not only made money in both bull and bear markets, but regularly beaten their respective benchmarks. To do this over a decade or more indicates more than a random distribution of performance, or indeed luck.

The problem in trying to prove that the market is not random is simply that an approach that might work for a statistically valid period of analysis may suddenly become useless once it is widely known. This is because the edge the trader might have had in pricing will be negated if many more participants influence the opening and closing prices that are achieved by their participation. The great majority of studies of technical theories have found the strategies to be completely useless in predicting very long term prices of securities, but there continue to be technical anomalies that occur regularly, and it is up to the smart trader to constantly search for that edge to ‘beat’ the market.

The other point that has been put forward by proponents of efficient markets is that if one takes a random distribution of fund managers, it is not possible for more than half to beat the respective benchmark. Because of costs, using an active manager will on average do less well than simply matching the benchmark using a passive or tracking fund. Whilst this cannot be disputed, there are two important points: first, using a long-side only tracking fund for instance will cause losses in a bear market. Second, successful money or fund mangers tend on average to continue to beat their benchmark over time, and it is possible to have the talent to beat the market in the long term. Just ask Warren Buffett.

Proof the market is not random – a simple comparison against a major theory

The New York Times on 6th Sept 1998 noted a study that was published in the US Journal of Finance by Stephen Brown of New York University, William Goetzmann of Yale, and Alok Kumar of the University of Notre Dame. They tested the widely known Dow Theory system against a simple buy-and-hold strategy for the period from 1929 to 1998 on the US stockmarket.

Over the 70-year period, the Dow Theory system outperformed the buy and hold strategy by about 2% per year. In addition, the former’s portfolio carried significantly less risk, and risk-adjusted, the margin of outperformance would have been even greater.

Another way of looking at it is to consider the markets both efficient and predictable. In a debunk of the earlier work, Lo and Mackinlay’s “A Non-Random Walk Down Wall Street” book concluded that in reality, markets were neither perfectly efficient nor completely inefficient. All markets were efficient to a certain extent, some more so than others. Rather than being an issue of black or white, market efficiency was more a matter of shades of grey, and in markets with substantial impairments of efficiency, more knowledgeable investors could strive to outperform less knowledgeable ones.

Conclusion

Just like predicting the weather, which still cannot be done with any great accuracy over more than a few days, it is difficult and almost impossible to predict future share prices. There are however patterns of human behaviour which are predictable, whether these correspond to the cycle of business investment and profits, how fear and greed manifests itself, and how traders react to outside news events.

All these inputs make it possible for a dedicated CFD trader to achieve outperformance by exploiting regular market anomalies and seeking out the best probability trades.
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