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Do stockmarkets act in a random manner?

Whatever sphere of investment is involved, whether it is stockmarket trading, CFDs, forex, bonds or commodities, the question of whether or not markets are random has intrigued some analysts for many years.

As a dedicated advisory broker, our view which can be backed up by our own research, is of course that action in the market is not wholly random. We do accept however that there are periods, usually short term, where chaotic action takes place with little relation to the underlying fundamentals of supply and demand.

Nevertheless, it is an intriguing subject and as a client trading stockmarket CFDs, there would be no point in playing the game if it was purely random. Over the years there have been many other 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. These have shown that there is often a distinct repetition of patterns both in price and time cycles, which effectively confirm that price movements are not random.

Charts often exhibit similar pattern behaviour in many different asset classes aswell as share prices, but 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 detailed 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 were independent of each other and had 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” had 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 and one that might be true, but does not explain human nature or supply and demand changes.

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 dismissed all analysis as futile, whether it was technical or fundamental.

Clearly when a trader takes a market or share 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.

Another aspect is the fractal nature of markets, where similar price moves and patterns can be observed over many different time frames, from minute by minute to multi year patterns.



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, a long term by any measure.

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.

Mike Estrey
Head of Research at Blue Index, the Online CFD Trading experts
09/01/2008

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