Search results

Outlines the development of genetic algorithms (GA), explains how they generate solutions to problems and applies four GA models incorporating different factors (e.g. risk, transaction costs etc.) to financial investment strategies. Uses 1987‐1996 share price data from the Madrid Stock Exchange (Spain) and a buy‐and‐hold strategy in the IBEX‐35 index as a benchmark. Shows that all four GA models generat superior daily returns of long positions with lower risk; and discusses the variations between them in detail.