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When discussing market analysis, we generally consider the two contending schools of thought to be Fundamental Analysis and Technical Analysis. However, in the early 1970's, there emerged a third view known as the "Random Walk Theory", which was not so much an approach to market analysis as it was a critique of the other two methods. The Random Walk Theory is the popular name for a market model known in academic circles as Efficient Market Theory. This model of the market contends that prices are "efficient" in the sense that all known information and market expectations are immediately factored into the market through the movement of prices. But these price movements are caused by so many different factors that they become random in nature, and the only thing that we can be sure of is that the present price is the correct one because it is based on all known information. We cannot, according to EMT, reliably predict the movement of prices which keeps the market at this point. This model centers around the Efficient Market Hypothesis, of which there are three versions; the weak, the semi-strong, and the strong. In terms of using analysis techniques to outperform the market consistently, the weak version basically says that technical analysis cannot work, the semi-strong says that neither technical analysis nor fundamental analysis can work, and the strong version says that nothing, not even illegal inside information, will work! More recent academic developments such as Behavioral Finance have presented strong arguments against the EMH, and in my view the hypothesis is not valid even in its weak form. My purpose in this article is not to argue against the merits of the Random Walk Theory however, but to voice some concerns about the tone of the debate. In my own view, one of the historical effects of the Efficient Market Hypothesis has been an unfortunate level of animosity between trading professionals (especially technical analysts) and the academic community. The condescending attitudes of some academics such as Burton Malkiel, the author of "A Random Walk Down Wall Street" toward the field of TA has tended to exacerbate this schism. Allow me a brief rant on "A Random Walk Down Wall Street". While most of Malkiel's book is scholarly and objective in tone, this goes out the window when he discusses technical analysts. The book has a section called "Holes in their shoes and ambiguity in their forecasts" where he makes the claim that he has never met a successful technical analyst. He lumps chart reading in with astrology and market superstitions like the hemline indicator and the Super Bowl indicator. In one well known part of the book, he describes an incident in which he supposedly duped a technical analyst with a chart made from the results of coin tosses. According to Malkiel, when this unidentified analyst saw the chart, he immediately asked what stock it was so that he could hurry out and buy some right away. He then became angry when told it was a chart of random coin tosses. While I'm not aware of any evidence that this story is contrived, this strikes me as more of a wishful fantasy on Malkiel's part than an actual event. If not, then he certainly picked the most neurotic and unobservant technical analyst he could find to validate his stunt (the chart was very odd looking because all the closes were either at the high or low for the day and all the daily ranges were equal). This sort of thing is not helpful. While I agree that technical analysis in its classical form is not satisfactory, I believe that its practitioners should be supported and educated by the academic community...not ridiculed by them. It has become clear that the EMH is not widely applicable to markets in the real world. There are trading opportunities which arise in markets and persist for long enough periods of time for traders to profit from them, if they have the correct tools to find and validate these opportunities. The academic world and the trading world can and should work more closely together to explore these possibilities and develop these tools.
Scott Percival
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