Xiaowei Zhang, Jose Blanchet, Kay Giesecke, Peter W. Glynn (2015) Affine Point Processes: Approximation and Efficient Simulation. Mathematics of Operations Research 40(4):797-819.
Abstract
We establish a central limit theorem and a large deviations principle for affine point processes, which are stochastic models of correlated event timing widely used in finance and economics. These limit results generate closed-form approximations to the distribution of an affine point process. They also facilitate the construction of an asymptotically optimal importance sampling estimator of tail probabilities. Numerical tests illustrate our results.
Authors
Xiaowei Zhang, Jose Blanchet, Kay Giesecke, Peter W Glynn
Publication date
2015/10
Journal
Mathematics of Operations Research
Volume
40
Issue
4
Pages
797-819
Publisher
INFORMS
