We explore the Monte Carlo steps required to reduce the sampling error of the estimated 99.9% quantile within an acceptable threshold. Our research is of primary interest to practitioners working in the area of operational risk measurement, where the annual loss distribution cannot be...

The two basic questions that every investor tries to answer before investment are questions about predicting return and risk. Risk and return are generally considered two positively correlated sizes, during the growth of risk it is expected increase of return to compensate the higher risk. The...

In this paper, we propose a novel framework for estimating systemic risk measures and risk allocations based on Markov Chain Monte Carlo (MCMC) methods. We consider a class of allocations whose jth component can be written as some risk measure of the jth conditional marginal loss distribution...