Thinly traded securities exist in both emerging and well developed markets. However, plausible estimations of market risk measures for portfolios with infrequently traded securities have not been explored in the literature. We propose a methodology to calculate market risk measures based on the...

A flexible framework for the analysis of tail events is proposed. The framework contains tail moment measures that allow for Expected Shortfall (ES) estimation. Connecting the implied tail thickness of a family of distributions with the quantile and expectile estimation, a platform for risk...

Internationally operating firrns naturally face the decision whether or not to hedge the currencyrisk implied by foreign investments. In a recent paper, Bos, Mahieu and van Dijk (2000) evaluatethe returns from optimal and alternative currency hedging strategies, for a series of 7 models,using...

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...

This paper investigates the factors influencing banks' decision to engage in advanced risk management, from both a theoretical and an empirical perspective. In recent decades, credit risk management in banks has become highly sophisticated and banks have become more active and advanced in the...

Thinly traded securities exist in both emerging and well developed markets. However, plausible estimations of market risk measures for portfolios with infrequently traded securities have not been explored in the literature. We propose a methodology to calculate market risk measures based on the...

Stochastic discounting models are generally recognized as extremely strong analytical tools for a very wide variety of fundamental areas in the actuarial discipline. The paper is mainly devoted to the formulation, investigation and application in the actuarial discipline of a stochastic...