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Copula function approaches for the analysis of serial and cross dependence in stock returns

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  • Rivieccio, Giorgia
  • De Luca, Giovanni

Abstract

The description of the dynamic behavior of multiple time series represents an important point of departure to obtain accurate forecasts both in economic and financial analysis. We provide a method for the comparison of the out-of-sample performance of portfolios, respectively, ignoring and exploiting serial and cross dependence in stock returns. The serial and cross dependence is modeled using both the classical linear and easy-to-use Vector AutoRegressive and more sophisticated models making use of copula functions. After deriving the classical and copula-based VAR conditional expected returns and covariance, we construct different portfolios and compare them in terms of Sharpe ratio in an out-of-sample period.

Suggested Citation

  • Rivieccio, Giorgia & De Luca, Giovanni, 2016. "Copula function approaches for the analysis of serial and cross dependence in stock returns," Finance Research Letters, Elsevier, vol. 17(C), pages 55-61.
    • Handle: RePEc:eee:finlet:v:17:y:2016:i:c:p:55-61
    DOI: 10.1016/j.frl.2016.01.006
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    1. repec:bla:jfinan:v:53:y:1998:i:6:p:1975-1999 is not listed on IDEAS
    2. Victor DeMiguel & Francisco J. Nogales & Raman Uppal, 2014. "Stock Return Serial Dependence and Out-of-Sample Portfolio Performance," The Review of Financial Studies, Society for Financial Studies, vol. 27(4), pages 1031-1073.
    3. Carluccio Bianchi & Alessandro Carta & Dean Fantazzini & Maria Elena De Giuli & Mario Maggi, 2010. "A copula-VAR-X approach for industrial production modelling and forecasting," Applied Economics, Taylor & Francis Journals, vol. 42(25), pages 3267-3277.
    4. Lo, Andrew W & MacKinlay, A Craig, 1990. "When Are Contrarian Profits Due to Stock Market Overreaction?," The Review of Financial Studies, Society for Financial Studies, vol. 3(2), pages 175-205.
    5. Eike Christian Brechmann & Claudia Czado, 2015. "COPAR—multivariate time series modeling using the copula autoregressive model," Applied Stochastic Models in Business and Industry, John Wiley & Sons, vol. 31(4), pages 495-514, July.
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    Cited by:

    1. Toan Luu Duc Huynh & Tobias Burggraf, 2020. "If worst comes to worst: Co-movement of global stock markets in the US-China trade war," Economics and Business Letters, Oviedo University Press, vol. 9(1), pages 21-30.
    2. Huynh, Toan Luu Duc & Hille, Erik & Nasir, Muhammad Ali, 2020. "Diversification in the age of the 4th industrial revolution: The role of artificial intelligence, green bonds and cryptocurrencies," Technological Forecasting and Social Change, Elsevier, vol. 159(C).

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    More about this item

    Keywords

    Copula function; Sharpe ratio; Vector AutoRegressive models;
    All these keywords.

    JEL classification:

    • C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General
    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • G11 - Financial Economics - - General Financial Markets - - - Portfolio Choice; Investment Decisions

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