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.
Bibliographical noteVolume 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.
- Conditional correlation
- cross hedging
- dynamic conditional correlation (DCC)
- hedge ratio