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http://dx.doi.org/10.11627/jksie.2022.45.3.123

Clustering-driven Pair Trading Portfolio Investment in Korean Stock Market  

Cho, Poongjin (Department of Industrial Engineering, Hanyang University)
Lee, Minhyuk (Department of Business Administration, Pusan National University)
Song, Jae Wook (Department of Industrial Engineering, Hanyang University)
Publication Information
Journal of Korean Society of Industrial and Systems Engineering / v.45, no.3, 2022 , pp. 123-130 More about this Journal
Abstract
Pair trading is a statistical arbitrage investment strategy. Traditionally, cointegration has been utilized in the pair exploring step to discover a pair with a similar price movement. Recently, the clustering analysis has attracted many researchers' attention, replacing the cointegration method. This study tests a clustering-driven pair trading investment strategy in the Korean stock market. If a pair detected through clustering has a large spread during the spread exploring period, the pair is included in the portfolio for backtesting. The profitability of the clustering-driven pair trading strategies is investigated based on various profitability measures such as the distribution of returns, cumulative returns, profitability by period, and sensitivity analysis on different parameters. The backtesting results show that the pair trading investment strategy is valid in the Korean stock market. More interestingly, the clustering-driven portfolio investments show higher performance compared to benchmarks. Note that the hierarchical clustering shows the best portfolio performance.
Keywords
Pair trading; Clustering; Statistical Arbitrage; Investment Strategy;
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