Recent crises in the financial industry have shown weaknesses in the modeling of Risk-Weighted Assets (RWAs). Relatively minor model changes may lead to substantial changes in the RWA numbers. Similar problems are encountered in the Value-at-Risk (VaR)-aggregation of risks. In this article, we highlight some of the underlying issues, both methodologically, as well as through examples. In partic...

Modeling high-dimensional dependence is widely studied to explore deep relations in multiple variables particularly useful for financial risk assessment. Very often, strong restrictions are applied on a dependence structure by existing high-dimensional dependence models. These restrictions disabled the detection of sophisticated structures such as asymmetry, upper and lower tail dependence betw...

We discuss the CreditRisk+ methodology from the perspective of the moment generating function of the credit factors. This representation lends itself to a new recursion formula for the portfolio loss distribution that is more accurate and considerably faster, particularly for large portfolios. We discuss how the model can be extended to incorporate correlations between risk factors and derive t...

Maximum Relative Drawdown measures the largest percentage drop of the price process on a given time interval. More recently, Maximum Relative Drawdown has become more popular as an alternative measure of risk. In contrast to the Value at Risk measure, it captures the path property of the price process. In this article, we propose a partial differential equation approach to determine the theoret...

The traditional Value at Risk (VaR) is a very popular tool measuring market risk, but it does not incorporate liquidity risk. This paper proposes an extended VaR model to integrate liquidity risk for intraday trading strategies using high frequency order book data. We estimate the one step ahead liquidity adjusted intraday VaR called(LAIVaR) for both bid and ask positions, considering several t...

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...

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....