Variance Reduction in Hull-White Using Moment Matching
Variance reduction refers to techniques or methods aimed at reducing the variance, or variability, of the output of a statistical estimator or simulation.
Moment matching is a technique used in statistics and probability theory to adjust the parameters of a distribution so that it matches certain moments of another distribution.
I explained the concepts of variance reduction and moment matching and why we use them.
Then I demonstrated how my model used moment matching for variance reduction.
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The Python code is uploaded into https://github.com/AIMLModeling/Momen...