A new correlation coefficient for bivariate time-series data

Orhan Erdem, Elvan Ceyhan and Yusuf Varlı

Physica A: Statistical Mechanics and its Applications, 2014, vol. 414, issue C, 274-284

Abstract: The correlation in time series has received considerable attention in the literature. Its use has attained an important role in the social sciences and finance. For example, pair trading in finance is concerned with the correlation between stock prices, returns, etc. In general, Pearson’s correlation coefficient is employed in these areas although it has many underlying assumptions which restrict its use. Here, we introduce a new correlation coefficient which takes into account the lag difference of data points. We investigate the properties of this new correlation coefficient. We demonstrate that it is more appropriate for showing the direction of the covariation of the two variables over time. We also compare the performance of the new correlation coefficient with Pearson’s correlation coefficient and Detrended Cross-Correlation Analysis (DCCA) via simulated examples.

Keywords: Cross-correlation; Pearson’s correlation coefficient; DCCA; Stationarity; Non-stationary time series (search for similar items in EconPapers)
Date: 2014
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Citations: View citations in EconPapers (6)

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Related works:
Working Paper: A New Correlation Coefficient for Bivariate Time-Series Data (2011)
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Persistent link: https://EconPapers.repec.org/RePEc:eee:phsmap:v:414:y:2014:i:c:p:274-284

DOI: 10.1016/j.physa.2014.07.054

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