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Testing Linearity in an AR Errors-in-variables Model with Application to Stochastic Volatility

D. FeldmannW. HärdleC. HafnerM. HoffmannO. LepskiA. Tsybakov — 2003

Applicationes Mathematicae

Stochastic Volatility (SV) models are widely used in financial applications. To decide whether standard parametric restrictions are justified for a given data set, a statistical test is required. In this paper, we develop such a test of a linear hypothesis versus a general composite nonparametric alternative using the state space representation of the SV model as an errors-in-variables AR(1) model. The power of the test is analyzed. We provide a simulation study and apply the test to the HFDF96...

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