Estimating Discretely Observed Diffusions
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In many areas of application the estimation of parameters in SDEs is an important practical task. This estimation is almost like inverting the problem of scenario simulation and can benefit from the application of Wagner-Platen expansions. We have already mentioned that it is important to apply scenario simulation when checking empirically the usefulness of a proposed estimation methods. This chapter introduces estimation techniques for discretely observed diffusion processes. Transform functions are applied to the data in order to obtain estimators of both the drift and diffusion coefficients. Consistency and asymptotic normality of the resulting estimators is investigated. Power transforms are used to estimate the parameters of affine diffusions, for which explicit estimators are obtained.
KeywordsAsset Price Estimate Function Maximum Likelihood Estimator Transition Density Conditional Moment
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