Estimation of stochastic volatility models with diagnostics
Date
1997-11-01
Authors
Journal Title
Journal ISSN
Volume Title
Repository Usage Stats
views
downloads
Abstract
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.
Type
Department
Description
Provenance
Subjects
Citation
Permalink
Collections
Scholars@Duke
George E. Tauchen
George Tauchen is the William Henry Glasson Professor of Economics and professor of finance at the Fuqua School of Business. He joined the Duke faculty in 1977 after receiving his Ph.D. from the University of Minnesota. He did his undergraduate work at the University of Wisconsin. Professor Tauchen is a fellow of the Econometric Society, the American Statistical Association, the Journal of Econometrics, and the Society for Financial Econometrics (SoFie). He is also the 2003 Duke University Scholar/Teacher of the Year. Professor Tauchen is an internationally known time series econometrician. He has developed several important new techniques for making statistical inference from financial time series data and for testing models of financial markets. He has given invited lectures at many places around the world, including London, Paris, Beijing, Taipei, Hong Kong, and Sydney. His current research (with Professor Li of Duke) examines the impact of large jump-like moves in stock market returns on the returns of various portfolios and individual securities. He is a former editor of the Journal of Business and Economic Statistics (JBES) and former associate editor of Econometrica, Econometric Theory, The Journal of the American Statistical Association (JASA), and JBES. He is currently Co-Editor of the Journal of Financial Econometrics.
Unless otherwise indicated, scholarly articles published by Duke faculty members are made available here with a CC-BY-NC (Creative Commons Attribution Non-Commercial) license, as enabled by the Duke Open Access Policy. If you wish to use the materials in ways not already permitted under CC-BY-NC, please consult the copyright owner. Other materials are made available here through the author’s grant of a non-exclusive license to make their work openly accessible.