Asymmetry in tail dependence in equity portfolios

Asymmetry in Tail Dependence in Equity Portfolios (Technical Appendix)

Commodity and equity markets: Some stylized facts from a copula approach

In this paper, we propose to identify the dependence structure that exists between returns on equity and commodity futures and its development over the past 20 years. The key point is that we do not impose any dependence structure, but let the data select it. To do so, we model the dependence between commodity (metal, agriculture and energy) and stock markets using a flexible approach that allo...

Modeling Dependence Structure and Forecasting Market Risk with Dynamic Asymmetric Copula∗

We investigate the dynamic and asymmetric dependence structure between equity portfolios from the US and UK. We demonstrate the statistical significance of dynamic asymmetric copula models in modelling and forecasting market risk. First, we construct “high-minus-low" equity portfolios sorted on beta, coskewness, and cokurtosis. We find substantial evidence of dynamic and asymmetric dependence b...

Why optimal diversification cannot outperform naive diversification: Evidence from tail risk exposure

Version of January 2013 Abstract This paper examines the outperformance of naive diversification relative to optimal diversification. From out-of-sample analysis using portfolios consisting of individual stocks as well as diversified equity portfolios, we find that optimal diversification fails to consistently outperform naive diversification. Our results show that naive diversification increas...

Dynamic Dependence and Diversification in Corporate Credit∗

We characterize dependence and tail dependence in corporate credit using a new class of dynamic copula models which can capture dynamic dependence and asymmetry in large samples of firms. We also document important differences between the dependence dynamics for credit spreads and equity returns. Modeling a decade of weekly CDS spreads for 215 firms, we find that copula correlations are highly ...