ECGA vs. BOA in discovering stock market trading experts

This paper presents two evolutionary algorithms, ECGA and BOA, applied to constructing stock market trading expertise, which is built on the basis of a set of specific trading rules analysing financial time series of recent price quotations. A few modifications of ECGA are proposed in order to reduce the computing time and make the algorithm applicable for real-time trading. In experiments carried out on real data from the Paris Stock Exchange, the algorithms were compared in terms of the efficiency in solving the optimization problem, in terms of the financial relevance of the investment strategies discovered as well as in terms of the computing time. Categories and Subject Descriptors I.2 [Artificial Intelligence]: Applications and Expert Systems; I.2 [Artificial Intelligence]: Learning; J.1 [Computer Applications]: Administrative Data Processing—Financial General Terms Experimentation Keywords estimation of distribution algorithms, extended compact genetic algorithm, bayesi...

• Type: Conference
• Year: 2007
• Where: GECCO
• Authors: Piotr Lipinski
• Keywords: Computing Time, GECCO 2007, Stock Market Trading, financial Time Series