The No-Arbitrage model by Schonbucher [30] is combined with the Extended Vasicek Term Structure Model and applied to the pricing of DM-Eurobonds issued by sovereigns from emerging economies. Practical hedging according to the model is investigated. A portfolio of DM-Eurobonds is analyzed using the risk measures "Shortfall" and "Value at Risk".

We consider an enhancement of the credit risk+ model to incorporate correlations between sectors. We model the sector default rates as linear combinations of a common set of independent variables that represent macro-economic variables or risk factors. We also derive the formula for exact VaR contributions at the obligor level.

Banks and other financial institutions across the world use various approaches to quantify risk in their portfolios. Regulators require that value at risk (VaR), calculated based on the historical data, be used for certain reporting and capital allocation purposes. Currently, this simple risk measure, historical VaR or HsVaR, is computed by some firms using the full revaluation method, which is...

empirical studies show that there is stronger dependency between large losses than large profit in financial market, which undermine the performance of using symmetric distribution for modeling these asymmetric. that is why the assuming normal joint distribution of returns is not suitable because of considering the linier dependence, and can be lead to inappropriate estimate of var. copula theo...

A recent paper by Prékopa (2012) presented results in connection with Multivariate Value-at-Risk (MVaR) that has been known for some time under the name of p-quantile or p-Level Efficient Point (pLEP) and introduced a new multivariate risk measure, called Multivariate Conditional Value-at-Risk (MCVaR). The purpose of this paper is to further develop the theory and methodology of MVaR and MCVaR....

In this paper, the large deviation approach for computing the capital charge for operational risk of a bank is explored. Firstly, the negatively-associated structure is utilized to measure the dependence between distinct operational loss cells. Secondly, the lower and upper bounds of the tail distribution function of total aggregated loss processes are determined. In addition, first order appro...

Denote by X the set of actuarial risks, and let 0 ≤ X ∈ X be a random variable rv with cumulative distribution function cdf F x , decumulative distribution function ddf F x 1 − F x , and probability density function pdf f x . The functional H : X → 0,∞ is then referred to as a risk measure, and it is interpreted as the measure of risk inherent in X. Naturally, a quite significant number of risk...

A four-dimensional variational (4D-Var) data assimilation method is implemented in an improved intermediate coupled model (ICM) of the tropical Pacific. A twin experiment is designed to evaluate the impact of the 4D-Var data assimilation algorithm on ENSO analysis and prediction based on the ICM. The model error is assumed to arise only from the parameter uncertainty. The “observation” of the S...

Risk adjusted performance measurement for a portfolio involves calculating the contributions to total economic capital for sub-portfolios or single assets. We show that there is only one definition for the contributions which is suitable for performance measurement, namely as derivative of the underlying risk measure with respect to the weight of the considered sub-portfolio or asset. We review...

In credit risk management, migration or transition matrices are major inputs for risk management, Credit Value-at-Risk or derivative pricing. After reviewing distance measures for migration matrices we propose some new directed difference indices to measure changes in migration behavior in a more risk-sensitive way. We quantify the changes of the classical distance measures and the new distance...