An Alternative Approach to Measure Co-Movement between Two Time Series

José Pedro Ramos-Requena, Juan Trinidad-Segovia () and Miguel Ángel Sánchez-Granero
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José Pedro Ramos-Requena: Departamento de Economía y Empresa, Universidad de Almería, Carretera Sacramento, s/n, 04120 La Cañada de San Urbano, Almería, Spain
Miguel Ángel Sánchez-Granero: Departamento de Matemáticas, Universidad de Almería, Carretera Sacramento, s/n, 04120 La Cañada de San Urbano, Almería, Spain

Mathematics, 2020, vol. 8, issue 2, 1-24

Abstract: The study of the dependences between different assets is a classic topic in financial literature. To understand how the movements of one asset affect to others is critical for derivatives pricing, portfolio management, risk control, or trading strategies. Over time, different methodologies were proposed by researchers. ARCH, GARCH or EGARCH models, among others, are very popular to model volatility autocorrelation. In this paper, a new simple method called HP is introduced to measure the co-movement between two time series. This method, based on the Hurst exponent of the product series, is designed to detect correlation, even if the relationship is weak, but it also works fine with cointegration as well as non linear correlations or more complex relationships given by a copula. This method and different variations thereaof are tested in statistical arbitrage. Results show that HP is able to detect the relationship between assets better than the traditional correlation method.

Keywords: Hurst exponent; pairs trading; correlation; co-movement (search for similar items in EconPapers)
JEL-codes: C (search for similar items in EconPapers)
Date: 2020
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