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Copula Estimation for Nonsynchronous Financial Data

Author

Listed:
  • Arnab Chakrabarti

    (Indian Institute of Management)

  • Rituparna Sen

    (Indian Statistical Institute)

Abstract

Copula is a powerful tool to model multivariate data. We propose the modelling of intraday returns of multiple financial assets through copula. The problem originates due to the asynchronous nature of intraday financial data. We propose a consistent estimator of the correlation coefficient in case of elliptical copula and show that the plug-in copula estimator is uniformly convergent. For non-elliptical copulas, we capture the dependence through Kendall’s Tau (leveraging the relation between copula parameter and Kendall’s tau). We demonstrate underestimation of the copula parameter and propose an alternative method to obtain an improved estimator. In simulations, the proposed estimator reduces the bias significantly for a general class of copulas. We apply the proposed methods to real data of several stock prices.

Suggested Citation

  • Arnab Chakrabarti & Rituparna Sen, 2023. "Copula Estimation for Nonsynchronous Financial Data," Sankhya B: The Indian Journal of Statistics, Springer;Indian Statistical Institute, vol. 85(1), pages 116-149, May.
    • Handle: RePEc:spr:sankhb:v:85:y:2023:i:1:d:10.1007_s13571-022-00276-3
    DOI: 10.1007/s13571-022-00276-3
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    1. repec:hal:journl:peer-00815564 is not listed on IDEAS
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    More about this item

    Keywords

    Asynchronicity; High-frequency data; Dependence structure; Correlation; Kendall’s Tau;
    All these keywords.

    JEL classification:

    • C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General
    • C18 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Methodolical Issues: General
    • C58 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Financial Econometrics

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