The use of GARCH models with stable Paretian innovations in financial modeling has been recently suggested in the literature. This class of processes is attractive because it allows for conditional skewness and leptokurtosis of financial returns without ruling out normality. This contribution...

The present study compares the performance of the long memory FIGARCH model, with that of the short memory GARCH specification, in the forecasting of multi-period Value-at-Risk (VaR) and Expected Shortfall (ES) across 20 stock indices worldwide. The dataset is comprised of daily data covering...

This paper proposes dynamic copula and marginals functions to model the joint distribution of risk factor returns affecting portfolios profit and loss distribution over a specified holding period. By using copulas, we can separate the marginal distributions from the dependence structure and...

Empirical studies have shown that a large number of financial asset returns exhibit fat tails and are often characterized by volatility clustering and asymmetry. Also revealed as a stylized fact is Long memory or long range dependence in market volatility, with significant impact on pricing and...

We present an analysis of VaR forecasts and P&L-series of all 13 German banks that used internal models for regulatory purposes in the year 2001. To this end, we introduce the notion of well-behaved forecast systems. Furthermore, we provide a series of statistical tools to perform our analyses....

How can investors unlock the returns on the electric vehicle industry? Available investment choices range from individual stocks to exchange traded funds. We select six representative assets and characterize the time-varying joint distribution of their returns by copula-GARCH models. They...