In this paper, an approximation of dynamic programming using sequential stochastic programming is introduced to solve long-term dynamic financial planning problems. We prove that by approximating the true asset return dynamics by a set of scenarios and re-solving the problem at every time-step,...

The model parameters in optimal asset allocation problems are often assumed to be deterministic. This is not a realistic assumption since most parameters are not known exactly and therefore have to be estimated. We consider investment opportunities which are modeled as local geometric Brownian...

The aim of this paper is to introduce a new property for good quantile or Value-at-Risk (VaR) estimators. We define probability unbiasedness for the α-quantile estimator from a finite amount of data (<inline-formula id="ILM0001"> <inline-graphic xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="rquf_a_469278_o_ilm0001.gif"/> </inline-formula>) for the distribution function <italic>F</italic> _θ with parameter θ such that the estimator also has this...