Financial Returns and E ¢ ciency as seen by an Arti cial Technical Analyst

We introduce trading rules which are selected by an arti…cially intelligent agent who learns from experience an Arti…cial Technical Analyst. It is shown that these rules can lead to the recognition of subtle regularities in return processes whilst reducing data-mining problems inherent in simple rules proposed as model evaluation devices. The relationship between the e¢ciency of …nancial markets and the e¢cacy of technical analysis is investigated and it is shown that the Arti…cial Technical Analyst can be used to provide a quanti…able measure of market e¢ciency. The measure is applied to the DJIA daily index from 1962 to 1986 and implications for the behaviour of traditional agents are derived. ¤The research leading to this paper was supported by a grant from I.K.Y.. Thanks are due to Buz Brock, Dave Cass, Alex Gumbel, Blake LeBaron, Mark Salmon and particularly Ramon Marimon for useful comments and suggestions on previous versions of this paper. Blake LeBaron is also thanked for providing the necessary data.