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doi: 10.18452/3486
handle: 10419/65295
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.
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
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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