Genetic algorithms as a tool for the formation and evolution of trading strategies in the securities market

Abstract

Subject. This article deals with the tools for the formation and evolution of trading strategies in the securities market. Objectives. The article aims to develop a mathematical framework and a formalized algorithm for the formation and evolution of trading strategies in the securities market. Methods. For the study, I used a genetic algorithm as an evolutionary optimization model. Results. The article presents an original mathematical description of a tool for the formation and evolution of strategies using genetic algorithms and a formalized algorithm sufficient for implementation in general-purpose programming languages. Conclusions and Relevance. The results obtained are the basis for further research in the field of autonomous evolution of trading strategies, and the described models will allow further research on the basis of specific software tools. The work is of practical value for private and institutional investors, for whom the trading strategy in the securities market is one of the fundamental aspects of their activities.