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Title

Bitcoin Algorithm Trading using Genetic Programming

Author

Monira Essa Aloud

Citation

Vol. 23  No. 7  pp. 210-218

Abstract

The author presents a simple data-driven intraday technical indicator trading approach based on Genetic Programming (GP) for return forecasting in the Bitcoin market. We use five trend-following technical indicators as input to GP for developing trading rules. Using data on daily Bitcoin historical prices from January 2017 to February 2020, our principal results show that the combination of technical analysis indicators and Artificial Intelligence (AI) techniques, primarily GP, is a potential forecasting tool for Bitcoin prices, even outperforming the buy-and-hold strategy. Sensitivity analysis is employed to adjust the number and values of variables, activation functions, and fitness functions of the GP-based system to verify our approach's robustness.

Keywords

Bitcoin market; Artificial Intelligence; Genetic Programming; Technical analysis; Trading rules.

URL

http://paper.ijcsns.org/07_book/202307/20230724.pdf