Long memory in volatility is a stylized fact found in most financial return series. This paper empirically investigates the extent to which interdependence in emerging markets may be driven by conditional short and long range dependence in volatility. We fit copulas to pairs of raw and filtered...

This paper is concerned with the efficient allocation of a set of financial assets and its successful management. Efficient diversification of investments is achieved by inputing robust pair-copulas based estimates of the expected return and covariances in the mean-variance analysis of...

Volatility plays an important role when managing risks, composing portfolios, and pricing financial instruments. However it is not directly observable, being usually estimated through parametric models such as those in the GARCH family. A more natural empirical measure of daily returns...

Purpose – This paper aims to statistically model the serial dependence in the first and second moments of a univariate time series using copulas, bridging the gap between theory and applications, which are the focus of risk managers. Design/methodology/approach – The appealing feature of the...

Purpose – Proposes a new covariance matrix robust estimator able to capture the correct orientation of the data and the large unconditional variance caused by occasional high volatility periods. Design/methodology/approach – Derives easy-to-compute estimates for the center and covariance...