Consider the portfolio problem of choosing the mix between stocks and bonds under a downside risk constraint. Typically stock returns exhibit fatter tails than bonds corresponding to their greater downside risk. Downside risk criteria like the safety first criterion therefore often select corner...

When measuring market risk, credit institutions and Alternative Investment Fund Managers may deviate from equally weighting historical data in their Value-at-Risk calculation and instead use an exponential time series weighting. The use of exponential weighting in the Value-at-Risk calculation...

The aim of this paper is to analyze the sensitivity of Value at Risk (VaR) with respect to portfolio allocation. We derive analytical expressions for the first and second derivatives of the Value at Risk, and explain how they can be used to simplify statistical inference and to perform a local...

We study the implications of the value at risk concept for the bank's optimum amount of equity capital under credit risk. The market value of loans is risky and lognormally distributed. We show that the required equity capital depends upon managerial and market factors. Furthermore, the bank's...

We study the implications of the value at risk concept for the bank's optimum amount of equity capital under credit risk. The market value of loans is risky and lognormally distributed. We show that the required equity capital depends upon managerial and market factors. Furthermore, the bank's...

This paper publishes results on the convergence for hedging strategies in the setting of incomplete financial markets.

This paper delevops a tools to analyse the ordering of concordance of random vectors.

This papfer deals with distributional free inference to test for positive quadrant dependence, i.e. for the probability that two variables are simultaneously small (or large) being at least as great as it would be were they dependent.

Accurate prediction of the frequency of extreme events is of primary importance in many financialapplications such as Value-at-Risk (VaR) analysis. We propose a semi-parametric method for VaRevaluation. The largest risks are modelled parametrically, while smaller risks are captured by the...