A calibration algorithm for simulation-based pricing models

Derivative pricing models require calibration to market conditions in order to determine quantities such as hedging positions and the prices of other instruments. For stochastic models and/or complex derivatives whose prices are not of an analytic form, prices must be computed via simulation and the calibration is more difficult. A method to facilitate the calibration of simulation-based pricing models is proposed. The algorithm uses a statistically designed experiment to select the points at which simulations are performed. The method is quite general as it is independent of the stochastic model for the underlying and allows for different objective functions that can incorporate information such as open interest and volume. Furthermore, market prices from European- and/or American-style derivatives covering a range of strike prices and maturities can be handled by this technique. Examples show the procedure is successful at calibrating well-known asset pricing models to both simulated and market data.