modelling that enables stochastic structural change in model parameters and on model estimation by Bayesian or non …-parametric kernel methods. In the context of the estimation of covariance matrices of large dimensional panels, such data requires … applicable in econometric analysis beyond estimation of large covariance matrices. We discuss the utility of the robust …

This paper decomposes the risk premia of individual stocks into contributions from systematic and idiosyncratic risks … the variance of idiosyncratic returns. The estimation is performed on a time series of returns and option prices from 2006 … 80% of the equity and variance risk premia, respectively. I provide a categorization of sectors based on the risk profile …

This paper examines optimal portfolio selection using quantile-based risk measures such as Valueat-Risk (VaR) and … Conditional Value-at-Risk (CVaR). We address the case of a singular covariance matrix of asset returns, which leads to an …

develop an extended Factor Augmented VAR model that simultaneously allows the estimation of a measure of uncertainty and its …