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EconStor
Research . 2002
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Testing the Diffusion Coefficient

Authors: Kleinow, Torsten;

Testing the Diffusion Coefficient

Abstract

In mathematical finance diffusion models are widely used and a variety of different parametric models for the drift and diffusion coefficient coexist in the literature. Since derivative prices depend on the particular parametric model of the diffusion coefficient function of the underlying, a misspecification of this function leads to misspecified option prices. We develop two tests about a parametric form of the diffusion coefficient. The finite sample properties of the tests are investigated in a simulation study and the tests are applied to the 7 -day Eurodollar rate, the German stock market index DAX and five German stocks. For all observed processes, we find in the empirical analysis that our tests reject all tested parametric models. We conclude that affine diffusion processes might not be appropriate to model the evolution of financial time series and that a successful model for a financial market should incorporate the history of the observed processes of additional sources of randomness like stochastic volatility models.

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Germany
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Keywords

Continuous-time financial models, stock market index, Empirical Likelihood, ddc:330, spot rate models, 330 Wirtschaft, Diffusion,Continuous-time financial models,Nonparametric methods,Kernel smoothing,Goodness of fit test,spot rate models,interest rate,stock market index,Empirical Likelihood, Diffusion, Goodness of fit test, C52, Nonparametric methods, Kernel smoothing, C14, C22, interest rate, C12, jel: jel:C52, jel: jel:C12, jel: jel:C22, jel: jel:C14

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
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