Financial risk control has always been challenging and becomes now an even harder problem as joint extreme events occur more frequently. For decision makers and government regulators, it is therefore important to obtain accurate information on the interdependency of risk factors. Given a...

In this study we consider the risk estimation as a stochastic process based on the Sample Quantile Process (SQP) - which is a generalization of the Value-at-Risk calculated on a rolling sample. Using SQP's, we are able to show and quantify the pro-cyclicality of the current way financial...

This paper presents the first methodological proposal of estimation of the Lambda VaR. Our approach is dynamic and calibrated to market extreme scenarios, incorporating the need of regulators and financial institutions in more sensitive risk measures. We also propose a simple backtesting...

This paper presents the first methodological proposal of estimation of the VaR. Our approach is dynamic and calibrated to market extreme scenarios, incorporating the need of regulators and financial institutions in more sensitive risk measures. We also propose a simple backtesting methodology by...

The severity function approach (abbreviated SFA) is a method of selecting adverse scenarios from a multivariate density. It requires the scenario user (e.g. an agency that runs banking sector stress tests) to specify a "severity function", which maps candidate scenarios into a scalar severity...

Financial risk control has always been challenging and becomes now an even harder problem as joint extreme events occur more frequently. For decision makers and government regulators, it is therefore important to obtain accurate information on the interdependency of risk factors. Given a...

Ever since the financial crisis of the banking system of 2008 - 2010 the paradigm that deposits or other exposures towards major banks are safe has been fundamentally questioned. This put industrial corporates, who to support their business usually need to manage significant cash holdings or...

Credit risk models used in quantitative risk management treat credit risk analysis conceptually like a single person decision problem. From this perspective an exogenous source of risk drives the fundamental parameters of credit risk: probability of default, exposure at default and the recovery...

We take issue with claims that the funding mix of banks, which makes them fragile and crisisprone, is efficient because it reflects special liquidity benefits of bank debt. Even aside from neglecting the systemic damage to the economy that banks' distress and default cause, such claims are...