Intelligent trading strategy based on improved directional change and regime change detection

TL;DR

This paper introduces an improved directional change method combined with regime change detection to enhance trading strategies, resulting in higher profits and lower risks in forex market experiments.

Contribution

It proposes a novel threshold selection technique for directional change, incorporating decay coefficients and Bayesian optimization, along with regime change detection using Hidden Markov Models.

Findings

Significant profit increase in forex trading simulations.

Reduced trading risk through regime change detection.

Enhanced generalization of directional change methodology.

Abstract

Previous research primarily characterized price movements according to time intervals, resulting in temporal discontinuity and overlooking crucial activities in financial markets. Directional Change (DC) is an alternative approach to sampling price data, highlighting significant points while blurring out noise details in price movements. However, traditional DC treated the thresholds of upward and downward trends with distinct intrinsic patterns as equivalent and preset them as fixed values, which are dependent on the subjective judgment of traders. To enhance the generalization performance of this methodology, we improved DC by introducing a modified threshold selection technique. Specifically, we addressed upward and downward trends distinctly by incorporating a decay coefficient. Further, we simultaneously optimized the threshold and decay coefficient using the Bayesian Optimization Algorithm (BOA). Additionally, we recognized the abnormal market state by regime change detection based on the Hidden Markov Model (RCD-HMM) to reduce the risk. Our Intelligent Trading Algorithm (ITA) was constructed based on above methods and the experiments were carried out on tick data from diverse currency pairs in the forex market. The experimental results showed a significant increase in profit and reduction in risk of DC-based trading strategies, which demonstrated the effectiveness of our proposed methods.