<p>This paper presents an examination of the generalized Hurst exponent (GHE) based pairs trading strategy applied to the cryptocurrency market throughout the years 2022 and 2023. Numerical findings of the study shows that the GHE strategy is remarkably effective in identifying lucrative investment prospects, even amid high volatility in the cryptocurrency market. In particular, the profitability of the GHE approach is demonstrated in terms of performance indicators (Sharpe ratio, Sortino ratio and the coefficient <InlineEquation ID="IEq1"> <InlineMediaObject> <ImageObject Color="BlackWhite" FileRef="10614_2025_11149_Article_IEq1.gif" Format="GIF" Height="16" Rendition="HTML" Resolution="72" Type="Linedraw" Width="24" /> </InlineMediaObject> <EquationSource Format="TEX">\(\varvec{R^2}\)</EquationSource> </InlineEquation>). The robustness of the approach is confirmed by the out-of-sample data applications, and it is revealed that the GHE strategy consistently outperforms alternative pair selection methods (Distance, Correlation and Cointegration). Moreover, to observe the impact of both high-frequency price series and volatility of markets on the GHE approach, we compare the statistical results obtained using daily data for cryptocurrencies with those for the Dow Jones and Nasdaq 100 index, and the results indicated that cryptocurrencies generated higher returns and a better risk-return relationship compared to traditional indices. Thus, this study validates the viability of the GHE approach, highlighting its capacity to adapt to diverse market conditions. These findings may be useful for investors to optimize their trading strategies and maximize the risk-return relationship.</p>

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Analysis Pairs Trading Strategy Applied to the Cryptocurrency Market

  • José Pedro Ramos-Requena,
  • Mahmut Bağcı

摘要

This paper presents an examination of the generalized Hurst exponent (GHE) based pairs trading strategy applied to the cryptocurrency market throughout the years 2022 and 2023. Numerical findings of the study shows that the GHE strategy is remarkably effective in identifying lucrative investment prospects, even amid high volatility in the cryptocurrency market. In particular, the profitability of the GHE approach is demonstrated in terms of performance indicators (Sharpe ratio, Sortino ratio and the coefficient \(\varvec{R^2}\) ). The robustness of the approach is confirmed by the out-of-sample data applications, and it is revealed that the GHE strategy consistently outperforms alternative pair selection methods (Distance, Correlation and Cointegration). Moreover, to observe the impact of both high-frequency price series and volatility of markets on the GHE approach, we compare the statistical results obtained using daily data for cryptocurrencies with those for the Dow Jones and Nasdaq 100 index, and the results indicated that cryptocurrencies generated higher returns and a better risk-return relationship compared to traditional indices. Thus, this study validates the viability of the GHE approach, highlighting its capacity to adapt to diverse market conditions. These findings may be useful for investors to optimize their trading strategies and maximize the risk-return relationship.