An empirical application of stochastic volatility models
AbstractThis paper studies the empirical performance of stochastic volatility models for twenty years of weekly exchange rate data for four major currencies. We concentrate on the effects of the distribution of the exchange rate innovations for both parameter estimates and for estimates of the latent volatility series. The density of the log of squared exchange rate innovations is modelled as a flexible mixture of normals. We use three different estimation techniques: quasi-maximum likelihood, simulated EM, and a Bayesian procedure. The estimated models are applied for pricing currency options. The major findings of the paper are that: (1) explicitly incorporating fat-tailed innovations increases the estimates of the persistence of volatility dynamics; (2) the estimation error of the volatility time series is very large; (3) this in turn causes standard errors on calculated option prices to be so large that these prices are rarely significantly different from a model with constant volatility. Â© 1998 John Wiley & Sons, Ltd.
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Bibliographic InfoPaper provided by Tilburg University in its series Open Access publications from Tilburg University with number urn:nbn:nl:ui:12-3131739.
Date of creation: 1998
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Publication status: Published in Journal of Applied Econometrics (1998) v.13, p.333-360
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Web page: http://www.tilburguniversity.edu/
Other versions of this item:
- Ronald J. Mahieu & Peter C. Schotman, 1998. "An empirical application of stochastic volatility models," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 13(4), pages 333-360.
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