news anymore, prices must fluctuate randomly. This important observation, combined with the notion that positive earnings are the reward for bearing risk, and the earlier empirical findings that successive price changes are independent, led to the efficient markets hypothesis. Especially the notion of trade-off between reward and risk distinguishes the efficient markets hypothesis from the random walk theory, which is merely a purely statistical model of returns.
The influential paper of Fama (1970) reviews the theoretical and empirical literature on the efficient markets model until that date. Fama (1970) distinguishes three forms of market efficiency. A financial market is called weak efficient, if no trading rule can be developed that can forecast future price movements on the basis of past prices. Secondly, a financial market is called semi-strong efficient, if it is impossible to forecast future price movements on the basis of publicly known information. Finally, a financial market is called strong efficient if on the basis of all available information, also inside information, it is not possible to forecast future price movements. Semi-strong efficiency implies weak-form efficiency. Strong efficiency implies semi-strong and weak efficiency. If the weak form of the EMH can be rejected, then also the semi strong and strong form of the EMH can be rejected. Fama (1970) concludes that the evidence in support of the efficient markets model is very extensive, and that contradictory evidence is sparse. The impact of the empirical findings on random walk behavior and the conclusion in academia that financial asset prices are and should be unforecastable was so large, that it took a while before new academic literature on technical trading was published. Financial analysts heavily debated the efficient markets hypothesis. However, as argued by academics, even if the theory of Samuelson would be wrong, then there are still many empirical findings of no forecastability.
Market technicians kept arguing that statistical tests of any kind are less capable of detecting subtle patterns in stock price data than the human eye. Thus Arditti and McCollough (1978) argued that if stock price series have information content, then technicians should be able to differentiate between actual price data and random walk data generated from the same statistical parameters. For each of five randomly chosen stocks from the NYSE in the year 1969 they showed 14 New York based CFAs (Chartered Financial Analyst, the CFA program is a globally recognized standard for measuring the competence and integrity of financial analysts) with more than five years of experience three graphs, the actual price series plus two random price series. The analysts were asked to pick the actual price series using any technical forecasting tool they wanted. The results reveal that the technicians were not able to make consistently correct selections. Thus Arditti and McCollough (1978) conclude that past price data provide little or no