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Volatility-dependent correlations: further evidence of when, where and how

Author

Listed:
  • Adam Clements

    (Queensland University of Technology)

  • Ayesha Scott

    (Auckland University of Technology)

  • Annastiina Silvennoinen

    (Queensland University of Technology)

Abstract

This paper expands on the usefulness of conditioning correlations on market volatility to generate forecasts of the covariance matrix in two contexts: within a single market and between several international markets. The dynamic conditional correlation family provides an illustration of the relationship between volatility and correlation. We use a portfolio allocation problem to compare covariance forecasts over a range of portfolio sizes and sub-samples of high and low market volatility. Findings confirm recent results for these models in comparable examples and extend these results through the two comprehensive out-of-sample analyses including large dimensional and international settings. This study furthers our understanding of the linkage between volatility and correlations and provides guidance for exploiting correlation’s dependence on volatility, emphasising its importance for differing market states and portfolio characteristics.

Suggested Citation

  • Adam Clements & Ayesha Scott & Annastiina Silvennoinen, 2019. "Volatility-dependent correlations: further evidence of when, where and how," Empirical Economics, Springer, vol. 57(2), pages 505-540, August.
    • Handle: RePEc:spr:empeco:v:57:y:2019:i:2:d:10.1007_s00181-018-1473-0
    DOI: 10.1007/s00181-018-1473-0
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    Cited by:

    1. Luc Bauwens & Edoardo Otranto, 2023. "Modeling Realized Covariance Matrices: A Class of Hadamard Exponential Models," Journal of Financial Econometrics, Oxford University Press, vol. 21(4), pages 1376-1401.
    2. Gaoxiu Qiao & Yangli Cao & Feng Ma & Weiping Li, 2023. "Liquidity and realized covariance forecasting: a hybrid method with model uncertainty," Empirical Economics, Springer, vol. 64(1), pages 437-463, January.
    3. Bauwens, Luc & Otranto, Edoardo, 2020. "Nonlinearities and regimes in conditional correlations with different dynamics," Journal of Econometrics, Elsevier, vol. 217(2), pages 496-522.
    4. Xi Zhang & Xu Wu & Linlin Zhang & Zhonglu Chen, 2022. "The Evaluation of Mean-Detrended Cross-Correlation Analysis Portfolio Strategy for Multiple risk Assets," Evaluation Review, , vol. 46(2), pages 138-164, April.

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    More about this item

    Keywords

    Volatility; Multivariate GARCH; Portfolio allocation; VIX; VSTOXX;
    All these keywords.

    JEL classification:

    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • G1 - Financial Economics - - General Financial Markets
    • G17 - Financial Economics - - General Financial Markets - - - Financial Forecasting and Simulation

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