A Range-Based Test for the Parametric Form of the Volatility in Diffusion Models
AbstractWe propose a new test for the parametric form of the volatility function in continuous time diffusion models of the type dXt = a(t,Xt)dt + s(t,Xt)dWt. Our approach involves a range-based estimation of the integrated volatility and the integrated quarticity, which are used to construct the test statistic. Under rather weak assumptions on the drift and volatility we prove weak convergence of the test statistic to a centered mixed Gaussian distribution. As a consequence we obtain a test, which is consistent for any fixed alternative. Moreover, we present a parametric bootstrap procedure which provides a better approximation of the distribution of the test statistic. Finally, it is demonstrated by means of Monte Carlo study that the range-based test is more powerful than the return-based test when comparing at the same sampling frequency.
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Bibliographic InfoPaper provided by School of Economics and Management, University of Aarhus in its series CREATES Research Papers with number 2007-26.
Date of creation: 19 Sep 2007
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Web page: http://www.econ.au.dk/afn/
Bipower Variation; Central Limit Theorem; Diffusion Models; Goodness-Of- Fit Testing; High-Frequency Data; Integrated Volatility; Range-Based Bipower Variation; Semimartingale Theory;
Other versions of this item:
- Mark Podolskij & Daniel Ziggel, 2008. "A Range-Based Test for the Parametric Form of the Volatility in Diffusion Models," CREATES Research Papers 2008-22, School of Economics and Management, University of Aarhus.
- C12 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Hypothesis Testing: General
- C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General
This paper has been announced in the following NEP Reports:
- NEP-ALL-2008-06-27 (All new papers)
- NEP-ETS-2008-06-27 (Econometric Time Series)
- NEP-FMK-2008-06-27 (Financial Markets)
- NEP-MST-2008-06-27 (Market Microstructure)
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