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An Objective Function for Simulation Based Inference on Exchange Rate Data

Peter Winker (), Manfred Gilli () and Vahidin Jeleskovic
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Vahidin Jeleskovic: Department of Economics, University of Giessen

No 07-01, Swiss Finance Institute Research Paper Series from Swiss Finance Institute

Abstract: The assessment of models of financial market behavior requires evaluation tools. When complexity hinders a direct estimation approach, e.g., for agent basedmicrosimulationmodels 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 (search for similar items in EconPapers)
JEL-codes: C14 C15 F31 (search for similar items in EconPapers)
New Economics Papers: this item is included in nep-ecm, nep-ifn and nep-mst
Date: 2007-02
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Journal Article: An objective function for simulation based inference on exchange rate data (2007) Downloads
Working Paper: An Objective Function for Simulation Based Inference on Exchange Rate Data (2006)
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