Asian Journal of Information Technology

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Trading Strategy Generation Using Genetic Algorithms

Jiah-Shing Chen
Page: 310-322 | Received 21 Sep 2022, Published online: 21 Sep 2022

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Abstract

Traditionally, trading strategies and their parameters are heuristically or subjectively constructed by their adopters. Recently, artificial intelligence techniques such as fuzzy logic, neural networks and genetic algorithms are used to solve various problems in trading. This study develops and implements a GA-based trading system which uses genetic algorithms to generate trading strategies based on technical indicators. Parameters of the technical indicators are determined by genetic algorithms using historical data. Simulation results using 4 technical indicators are presented to demonstrate the feasibility and effectiveness of our system.

How to cite this article:

Jiah-Shing Chen . Trading Strategy Generation Using Genetic Algorithms.
DOI: https://doi.org/10.36478/ajit.2005.310.322
URL: https://www.makhillpublications.co/view-article/1682-3915/ajit.2005.310.322