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- Title
Adaptive Control Variates for Finite-Horizon Simulation.
- Authors
Kim, Sujin; Henderson, Shane G.
- Abstract
Adaptive Monte Carlo methods are simulation efficiency improvement techniques designed to adaptively tune simulation estimators. Most of the work on adaptive Monte Carlo methods has been devoted to adaptively tuning importance sampling schemes. We instead focus on adaptive methods based on control variate schemes. We introduce two adaptive control variate methods, and develop their asymptotic properties. The first method uses stochastic approximation to adaptively tune control variate estimators. It is easy to implement, but it requires some nontrivial tuning of parameters. The second method is based on sample average approximation. Tuning is no longer required, but it can be computationally expensive. Numerical results for the pricing of barrier options are presented to demonstrate the methods.
- Subjects
MONTE Carlo method; ADAPTIVE control systems; STOCHASTIC approximation; STOCHASTIC processes; SELF-organizing systems; MATHEMATICAL models
- Publication
Mathematics of Operations Research, 2007, Vol 32, Issue 3, p508
- ISSN
0364-765X
- Publication type
Article
- DOI
10.1287/moor.1070.0251