Intelligent Stock Portfolio Management Using a Long-Term Fuzzy System

Abstract

The complexity of financial markets is driving researchers to multiply their efforts in order to improve their forecasting methods. This paper inoculates an old trading strategy with fuzzy subjective elements. The aim is to investigate whether the careful synthesis of a few long-term technical indicators, which have a different predictive philosophy, with an appropriately designed stock trading Mamdani fuzzy system, can produce satisfactory returns. More specifically, its purpose is to investigate whether the combination of moving averages, directional movement technical indicators and a fuzzified trading strategy can surpass the performance of buy and hold strategy (B&H). The proposed model has been tested in various (bull and bear) market environments for a period of more than 15 years, using the general index of ASE (Athens Stock Exchange). After taking into consideration transaction costs, it is found that the proposed model can produce better results (higher earnings) than the B&H strategy.