Evolutionary stock trading decision support system using sliding window

Abstract

A novel evolutionary decision support system (EDSS) eflective for making profitable trading decisions in the stock market is presented. Genetic algorithms is incorporated with a sliding window scheme to effective& estimate the most profitable trading decision, namely, Buy, Hold, or Sell. Because of its data-driven nature and genetic change to the positive course, EDSS bypasses the complicated steps of network establishment and subsequent training, and it can directly deal with the problem of structural instability that plaques traditional rule-based systems. Empirical tests are conducted on the weighted price index of Taiwan stock market (TSE WSIJCompared to the buy-and-hold strategy, EDSS can achieve signiJicant projit gaim improvement.