Can Neural Networks Learn the “Head and Shoulders“ Technical Analysis Price Pattern? Towards a Methodology for Testing the Efficient Market Hypothesis

Abstract

Testing the validity of the Efficient Market Hypothesis (EMH) has been an unsolved argument for the investment community. The EMH states that the current market price incorporates all the information available, which leads to a conclusion that given the information available, no prediction of the future price changes can be made. On the other hand, technical analysis, which is essentially the search for recurrent and predictable patterns in asset prices, attempts to forecast future price changes. To the extend that the total return of a technical trading strategy can be regarded as a measure of predictability, technical analysis can be seen as a test of the EMH and in particular of the independent increments version of random walk. This paper is an initial attempt on creating an automated process, based on a combination of a rule-based system and a neural network, of recognizing one of the most common and reliable patterns in technical analysis, the head and shoulders pattern. The systematic application of this automated process on the identification of the head and shoulders pattern and the subsequent analysis of price behavior, in various markets can in principle work as a test of the EMH.