In this study, we investigate the interactions of daily tail risk estimates thirty market indices representing a broad spectrum asset classes and geographies from 2003 till 2021 document important findings. Using step-by-step conditional copula with orthogonalized GARCH margins augmented further Markov-switching transitions, study dependence structure across classes. Our results predominantly i...

This study examines the portfolio optimization problem by exploiting daily data of 10 international Exchange Trade Funds (ETF) from 2012 to 2022. We extend Black-Litterman (BL) approach using ARMA-GARCH-copula-based expected returns as a proxy for investor views and use CVaR metric risk measure in procedure. The BL provides Bayesian methodology combining equilibrium produce returns. Regular Vin...

We use a time-varying copula model to investigate the impact of the introduction of the Euro on the dependence between seventeen European stock markets during the period 1994-2003. The model is implemented with a GJR-GARCH-t model for marginal distributions and the Gaussian copula for the joint distribution, which allows capturing time-varying, non-linear relationships. The results show that wi...