Journal of Econometrics

Volume 81, Issue 1, 01-November-1997

J. Econometrics Vol. 81 (1) pp. 159-192

Estimation of stochastic volatility models with diagnostics

a A. Ronald Gallant
b David Hsieh
b George Tauchen

a University of, North Carolina, NC, USA
b Department of Economics, Duke University, Social Science Building, Box 90097, Durham NC 27708-0097, USA


Efficient method of moments (EMM) is used to fit the standard stochastic volatility model and various extensions to several daily financial time series. EMM matches to the score of a model determined by data analysis called the score generator. Discrepancies reveal characteristics of data that stochastic volatility models cannot approximate. The two score generators employed here are `semiparametric ARCH' and `nonlinear nonparametric'. With the first, the standard model is rejected, although some extensions are accepted. With the second, all versions are rejected. The extensions required for an adequate fit are so elaborate that nonparametric specifications are probably more convenient. © 1997 Elsevier Science S.A.

JEL Classification: C14

Keyword(s): Stochastic volatility; Efficient method of moments (EMM); Diagnostics