Math 106 Stochastic processes

Week 8

Monte Carlo simulation/Importance sampling (4.2, 4.3, 4.4)

I reviewed the basics of Monte Carlo simulation and defined MSE and the bias–variance decomposition. Then I introduced the idea of importance sampling when working with probability densities.

Change of path measure (see 9.2)

I introduced the example of estimating the time to an event that occurs at a rate depending on an SDE. This motivated thinking about change of measure in path integrals and I discussed Girsanov’s theorem. I did not prove this, but gave a heuristic derivation.

Feynman-Kac formula

I derived the Feynman-Kac formula and discussed the particle interpretation of path integrals.

Notes: Importance sampling and path integrals