Integral equations, quasi-Monte Carlo methods and risk modelling
classification
🧮 math.PR
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applicationsequationsintegralnumericalriskachievedapproachbound
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We survey a QMC approach to integral equations and develop some new applications to risk modeling. In particular, a rigorous error bound derived from Koksma-Hlawka type inequalities is achieved for certain expectations related to the probability of ruin in Markovian models. The method is based on a new concept of isotropic discrepancy and its applications to numerical integration. The theoretical results are complemented by numerical examples and computations.
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