The variance implied conditional correlation

Andres Algaba*, Kris Boudt, Steven Vanduffel

*Corresponding author for this work

Research output: Contribution to JournalArticleAcademicpeer-review

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Abstract

We apply univariate GARCH models to construct a computationally simple filter for estimating the conditional correlation matrix of asset returns. The proposed Variance Implied Conditional Correlation (VICC) exploits the polarization result that links the correlation between two standardized variables with the variances of linear combinations thereof. In a Monte Carlo study, we show that the VICC yields accurate correlation estimates for common choices of the correlation dynamics. We also provide an empirical application to cross hedging that confirms the effectiveness of the VICC.

Original languageEnglish
Pages (from-to)200-222
Number of pages23
JournalEuropean Journal of Finance
Volume26
Issue number2-3
Early online date12 May 2019
DOIs
Publication statusPublished - 2020

Bibliographical note

Volume 26 (2020) Issue 2-3: Eighth International Conference on Mathematical and Statistical Methods for Actuarial Sciences and Finance, University Carlos III de Madrid, Madrid, 4-6th April 2018.

Keywords

  • Conditional correlation
  • cross hedging
  • dynamic conditional correlation (DCC)
  • GARCH
  • hedge ratio
  • regularization

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