International journal of advanced smart convergence

The Institute of Internet, Broadcasting and Communication (한국인터넷방송통신학회)
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P-Triple Barrier Labeling: Unifying Pair Trading Strategies and Triple Barrier Labeling Through Genetic Algorithm Optimization

  • Ning Fu (Dept. of Software Engineering, Jeonbuk National University) ;
  • Suntae Kim (Dept. of Software Engineering, Jeonbuk National University)
  • Received : 2023.10.11
  • Accepted : 2023.10.22
  • Published : 2023.12.31
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Abstract

In the ever-changing landscape of finance, the fusion of artificial intelligence (AI)and pair trading strategies has captured the interest of investors and institutions alike. In the context of supervised machine learning, crafting precise and accurate labels is crucial, as it remains a top priority to empower AI models to surpass traditional pair trading methods. However, prevailing labeling techniques in the financial sector predominantly concentrate on individual assets, posing a challenge in aligning with pair trading strategies. To address this issue, we propose an inventive approach that melds the Triple Barrier Labeling technique with pair trading, optimizing the resultant labels through genetic algorithms. Rigorous backtesting on cryptocurrency datasets illustrates that our proposed labeling method excels over traditional pair trading methods and corresponding buy-and-hold strategies in both profitability and risk control. This pioneering method offers a novel perspective on trading strategies and risk management within the financial domain, laying a robust groundwork for further enhancing the precision and reliability of pair trading strategies utilizing AI models.

Keywords

Acknowledgement

This research was supported by "Regional Innovation Strategy(RIS)" through the National Research Foundation of Korea(NRF) funded by the Ministry of Education(MOE)(2023RIS-008)

References

  1. Krauss, C. (2017). STATISTICAL ARBITRAGE PAIRS TRADING STRATEGIES: REVIEW AND OUTLOOK. Journal of Economic Surveys, 31(2), 513-545. https://doi.org/10.1111/joes.12153. 
  2. Chen, Huafeng, et al. "Empirical investigation of an equity pairs trading strategy." Management Science 65.1 (2019): 370-389.  https://doi.org/10.1287/mnsc.2017.2825
  3. Mudchanatongsuk, Supakorn, James A. Primbs, and Wilfred Wong. "Optimal pairs trading: A stochastic control approach." 2008 American control conference. IEEE, 2008. 
  4. M. Fil and L. Kristoufek, "Pairs Trading in Cryptocurrency Markets," in IEEE Access, vol. 8, pp. 172644-172651, 2020, doi: 10.1109/ACCESS.2020.3024619. 
  5. Kovacevic, Tomislav, et al. "Effect of labeling algorithms on financial performance metrics." 2022 45th Jubilee International Convention on Information, Communication and Electronic Technology (MIPRO). IEEE, 2022. 
  6. De Prado, Marcos Lopez. Advances in financial machine learning. John Wiley & Sons, 2018. 
  7. Kovacevic, Tomislav, et al. "Optimal Trend Labeling in Financial Time Series." IEEE Access (2023). 
  8. Khosravi, Morteza, and Majid Mirzaee Ghazani. "Novel insights into the modeling financial time-series through machine learning methods: Evidence from the cryptocurrency market." Expert Systems with Applications 234 (2023): 121012. 
  9. Van der Have, R., et al. "Pairs trading using machine learning: An empirical study." Erasmus School of Economics 12 (2017). 
  10. Mendelsohn, Louis B. Trend Forecasting with Intermarket Analysis: Predicting Global Markets with Technical Analysis. Vol. 92. John Wiley & Sons, 2012. 
  11. Cohen, Israel, et al. "Pearson correlation coefficient." Noise reduction in speech processing (2009): 1-4. 
  12. Hubrich, Kirstin, Helmut Lutkepohl, and Pentti Saikkonen. "A review of systems cointegration tests." Econometric Reviews 20.3 (2001): 247-318.  https://doi.org/10.1081/ETC-100104936
  13. Osifo, Ernest and Bhattacharyya, Ritabrata, Cryptocurrency Trading-Pair Forecasting, Using Machine Learning and Deep Learning Technique (March 5, 2020). Available at SSRN: https://ssrn.com/abstract=3610340 or http://dx.doi.org/10.2139/ssrn.3610340 
  14. Sharpe, William F. "The sharpe ratio." Streetwise-the Best of the Journal of Portfolio Management 3 (1998): 169-85.  https://doi.org/10.1515/9781400829408-022
  15. [Yahoo. Yahoo Finance Python Package. https://pypi.org/project/yfinance/, yfinance 0.2.27