Explorations in LCS Models of Stock Trading

In previous papers we have described the basic elements for building an economic model consisting of a group of artificial traders functioning and adapting in an environment containing real stock market information. We have analysed the feasibility of the proposed approach by comparing the final wealth generated by such agents over a period of time, against the wealth of a number of well known investment strategies, including the bank, buy-and-hold and trend-following strategies. In this paper we review classical economic theories and introduce a new strategy inspired by the Efficient Market Hypothesis (named here random walk to compare the performance of our traders. In order to build better trader models we must increase our understanding about how artificial agents learn and develop; in this paper we address a number of design issues, including the analysis of information sets and evolved strategies. Specifically, the results presented here correspond to the stock of IBM. 1 Fore...

• Type: Conference
• Year: 2001
• Where: IWLCS
• Authors: Sonia Schulenburg, Peter Ross
• Keywords: IWLCS 2001, Machine Learning, Markets, Real financial Markets, financial Markets