Efficient Monte Carlo Methods for Financial Risk Measures

The recent crisis in the global financial markets demands a critical review of current regulatory practice. Substantial efforts are required to devise efficient quantitative methods for a more reliable estimation of financial risks in the future. Unlike the currently used industry standards for risk evaluation, these tools must be able to detect extreme loss scenarios that are unlikely to occur but whose impact may be dramatic. In collaboration with Stefan Weber, we have developed a new Monte-Carlo technique for the efficient estimation of improved risk measures that are sensitive to the tails of loss distributions.