- We consider a general calibration problem for derivative pricing models. We reformulate the problem into a Bayesian framework to attain posterior distributions for calibration parameters. We give conditions on the value function under which the corresponding Bayesian estimator is consistent. Finally we apply our results to a discrete local volatility model and work through numerical examples to clarify the construction of Bayesian posteriors and its uses.
- Local pid: