23 Pages Posted: 21 Feb 2007
Date Written: February 19, 2007
The assessment of models of financial market behavior requires evaluation tools. When complexity hinders a direct estimation approach, e.g., for agent based microsimulation models or complex multifractal models, simulation based estimators might provide an alternative. In order to apply such techniques, an objective function is required, which should be based on robust statistics of the time series under consideration.
Based on the identification of robust statistics of foreign exchange rate time series in previous research, an objective function is derived. This function takes into account stylized facts about the unconditional distribution of exchange rate returns and properties of the conditional distribution, in particular, autoregressive conditional heteroscedasticity and long memory. A bootstrap procedure is used to obtain an estimate of the variance-covariancematrix of the different moments included in the objective function, which is used as a base for the weighting matrix.
Finally, the properties of the objective function are analyzed for two different agent based models of the foreign exchange market, a simple GARCH-model and a stochastic volatility model using the DM/US-$ exchange rate as a benchmark. It is also discussed how the results might be used for inference purposes.
Keywords: Indirect estimation, simulation based estimation, exchange rate returns
JEL Classification: C14, C15, F31
Suggested Citation: Suggested Citation
Gilli, Manfred and Winker, Peter and Jeleskovic, Vahidin, An Objective Function for Simulation Based Inference on Exchange Rate Data (February 19, 2007). Swiss Finance Institute Research Paper No. 07-01. Available at SSRN: https://ssrn.com/abstract=964131 or http://dx.doi.org/10.2139/ssrn.964131