Fuzzy logic based stock trading system

Abstract

The goal of this study was to build and to evaluate a human skill based fuzzy expert system for decision making support in a stock trading process. Our focus was concentrated on computer software that is capable to reproduce the knowledge from the skilled stock trader. Using classical technique and soft computing methods the expert system STRASS (Stock Trading Support System) was developed. The proposed system was tested for the historical collection of NASDAQ, NYSE and AMAX stock records. At present, it is being tested by "KOLEGU" mutual fund in a real stock trading process.