In this paper we explain how the importance sampling technique can be generalized from simulating expectations to computing the initial value of backward SDEs with Lipschitz continuous driver. By means of a measure transformation we introduce a variance reduced version of the forward...

An efficient and accurate approach is proposed for forecasting Value at Risk [VaR] and Expected Shortfall [ES] measures in a Bayesian framework. This consists of a new adaptive importance sampling method for Quantile Estimation via Rapid Mixture of t approximations [QERMit]. As a first step the...

This discussion paper resulted in a publication in the <I>International Journal of Forecasting</I> (2010). Vol. 26(2), 231-247.<P> An efficient and accurate approach is proposed for forecasting Value at Risk [VaR] and Expected Shortfall [ES] measures in a Bayesian framework. This consists of a new...</p></i>