Monte Carlo methods are now an essential part of the statistician's toolbox, to the point of being more familiar to graduate students than the measure theoretic notions upon which they are based! We recall in this note some of the advances made in the design of Monte Carlo techniques towards...

We propose a generic framework for the analysis of Monte Carlo simulation schemes of backward SDEs. The general results are used to re-visit the convergence of the algorithm suggested by Bouchard and Touzi (2004) [6]. By keeping the higher order terms in the expansion of the Skorohod integrals...

We propose a generic framework for the analysis of Monte Carlo simulation schemes of backward SDEs. The general results are used to re-visit the convergence of the algorithm suggested by Bouchard and Touzi (2004) [6]. By keeping the higher order terms in the expansion of the Skorohod integrals...

This paper deals with nonparametric inference for second order stochastic dominance of two random variables. If their distribution functions are unknown they have to be inferred from observed realizations. Thus, any results on stochastic dominance are in uenced by sampling errors. We establish...

This paper examines how uncertainty regarding future mortality and life expectancy outcomes, i.e. longevity risk, affects employer-provided defined benefit (DB) private pension plans liabilities. The paper argues that to assess uncertainty and associated risks adequately, a stochastic approach...

This paper provides a real option methodology for evaluating R&D investment opportunities assuming that potential competitors can en- ter in the market. As it is well known, R&D investments are made often in a phased manner and so each stage creates an opportunity (option) for subsequent...

A simple transform of a standard uniform variate is given for simulation of the maximum attained by a Wiener process with drift, conditioned upon the level attained by the process over an arbitrary time interval. The transform arises directly from inversion of the joint distribution function of...

We propose an approximate static hedging procedure for multivariate derivatives. The hedging portfolio is composed of statically held simple univariate options, optimally weighted minimizing the variance of the difference between the target claim and the approximate replicating portfolio. The...