Pairs trading, or statistical arbitrage, is an effective market-neutral trading strategy. Usually fundamental or quantitative analysis is used in order to determine which pairs are suitable for trading. We have previously discussed several pairs selection methods based on quantitative measures such as stock cointegration, correlation, pair distances, etc. Reference [1] introduced a new pairs selection method based on the Hurst exponent, One of the critical steps in [Pairs] Trading is the pairs selection, but not too much attention has been given to the stock universe before pairs selection. In this paper, we have introduced a preselection procedure based on the stocks comovement measure through comovement functions based on comovement studies on physical particle systems. Therefore, portfolios with less volatile stocks have been selected, and it has been observed that, with this new modification, [Pairs] Trading is also profitable in periods of low volatility. We find the paper interesting. Our comments are as follows,
Regarding the last bullet point, the authors also noted, However, on high volatility conditions, the strategy does not work as good. A plausible explanation of this phenomenon could be that, during periods with prolonged downward movements in the markets, volatility of the stocks is increased, and the model proposed in this paper is too slow to capture this faster change in the volatility of the preselected stocks. Regarding the first bullet point, we believe that the pairs selection method can be improved by further performing, e.g., a robustness test in order to minimize divergence risks. References [1] J. P. Ramos-Requena, M. N. López-García, M. A. Sánchez-Granero, J. E. Trinidad-Segovia, A Cooperative Dynamic Approach to Pairs Trading, Complexity, vol. 2021, Article ID 7152846, 2021. Originally Published Here: Using the Hurst Exponent and Stock Comovements for Pairs Trading
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