The potential for real-time testing of high-frequency trading strategies through a developed tool during volatile market conditions

• Autorzy: Vaitonis Mantas , Korovkinas Konstantinas

Identyfikatory

DOI

10.35784/acs-2023-15

• Języki publikacji: EN

Abstrakty

EN

This study presents a method for testing high-frequency trading (HFT) for algorithms on GPUs using kernel parallelization, code vectorization, and multidimensional matrices. The research evaluates HFT strategies within algorithmic cryptocurrency trading in volatile market conditions, particularly during the COVID-19 pandemic. The study's objective is to provide an efficient and comprehensive approach to assessing the efficiency and profitability of HFT strategies. The results show that the method effectively evaluates the efficiency and profitability of HFT strategies, as demonstrated by the Sharp ratio of 2.29 and the Sortino ratio of 2.88. The authors suggest that further study on HFT testing methods could be conducted using a tool that directly connects to electronic marketplaces, enabling real-time receipt of high-frequency trading data and simulation of trade decisions. Finally, the study introduces a novel method for testing HFT algorithms on GPUs, offering promising results in assessing the efficiency and profitability of HFT strategies during volatile market conditions.

Słowa kluczowe

EN

high frequency trading; cryptocurrencies; algorithmic trading; multidimensional matrice; parallelization; simulation

• Wydawca: Polskie Towarzystwo Promocji Wiedzy ; Lublin University of Technology
• Czasopismo: Applied Computer Science
• Rocznik: 2023
• Tom: Vol. 19, no 2
• Strony: 63--81
• Opis fizyczny: Bibliogr. 54 poz., fig., tab.

Twórcy

autor

Vaitonis Mantas

• Vilnius University, Kaunas Faculty, Institute of Social Sciences and Applied Informatics

• https://orcid.org/0000-0002-3760-6343

autor

Korovkinas Konstantinas

• Vilnius University, Kaunas Faculty, Institute of Social Sciences and Applied Informatics

• https://orcid.org/0000-0001-6111-3277

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