Optimization of High-frequency Pair Trading Algorithm Using a Combination of Genetic Algorithm and Fuzzy Statistical Quality Control

Subject Areas : Journal of Investment Knowledge

Mojtaba Dastori ^{1 *} , Saeed Moradpour ²

1 - Faculty Member of Department of Finance, Kish International Branch, Islamic Azad University, Kish, Iran.
2 - Faculty Member of Department of Finance, Faculty of Social Science, Bandar Abbas Branch, Islamic Azad University, Bandar Abbas, Iran.

Received: 2021-02-06 Accepted : 2018-07-10 Published : 2021-12-22

Keywords: High frequency trading, Pair trading, Genetic algorithm, Statistical Process Control,

Abstract :

In this study, the main problem is to improve the performance of the high-frequency pair trading algorithm by using a combination of genetic algorithm and fuzzy statistical quality control. For this purpose, two hypotheses have been developed. The statistical population is companies listed on the Tehran Stock Exchange, that statistical sample was limited to the top 50 companies due to the need for high-volume transactions, and 33 shares in 9 industries were selected. After implementing three basic methods, fuzzy statistical quality control and the combined genetic algorithm-fuzzy statistical quality control method, the performance results of the methods were compared with each other. The results showed that in the basic method 43.10% return, in the fuzzy statistical quality control method 55.58% return and in the combined genetic algorithm-fuzzy statistical quality control method the average return was 63.59%. In t-test, there is a statistically significant difference between the specific performance of the basic methods and fuzzy statistical quality control, as well as the basic methods and the combined genetic-fuzzy statistical algorithm quality control. Based on the results of fuzzy statistical quality control model and genetic algorithm, which has a significant increase compared to previous models in increasing the average return.

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