UvA-DARE is a service provided by the library of the University of Amsterdam (https://dare.uva.nl)
UvA-DARE (Digital Academic Repository)
Estimation and Inference with the Efficient Method of Moments: With
Applications to Stochastic Volatility Models and Option Pricing
van der Sluis, P.J.
Publication date
1999
Link to publication
Citation for published version (APA):
van der Sluis, P. J. (1999). Estimation and Inference with the Efficient Method of Moments:
With Applications to Stochastic Volatility Models and Option Pricing. Thela Thesis. TI
Research Series nr. 204.
General rights
It is not permitted to download or to forward/distribute the text or part of it without the consent of the author(s) and/or copyright holder(s), other than for strictly personal, individual use, unless the work is under an open content license (like Creative Commons).
Disclaimer/Complaints regulations
If you believe that digital publication of certain material infringes any of your rights or (privacy) interests, please let the Library know, stating your reasons. In case of a legitimate complaint, the Library will make the material inaccessible and/or remove it from the website. Please Ask the Library: https://uba.uva.nl/en/contact, or a letter to: Library of the University of Amsterdam, Secretariat, Singel 425, 1012 WP Amsterdam, The Netherlands. You will be contacted as soon as possible.
Volatility modelling and simulation-based estimation have attracted a great deal of research in econometrics and finance in recent years. Models for volatility arise in e.g. option pricing and risk management. Simulation-based estimation arises in cases where the likelihood function of a statistical model does not have an
analytically tractable expression. These two research topics blend together in the analysis of stochastic volatility models. A promising simulation-based estimation technique for stochastic volatility models is the Efficient Method of Moments (EMM).
In this book we evaluate the performance of EMM in the estimation of various stochastic volatility models through Monte Carlo experiments and empirical
applications with promising results. We also develop, analyze and apply EMM-based specification tests for structural stability in the context of stochastic volatility models. Furthermore we analyze option pricing under stochastic volatility and volatility forecasting. We find that allowing for (asymmetric) stochastic volatility reduces option pricing errors and explains the implied volatility smile, and that allowing for correlation between the volatilities in multivariate stochastic volatility models improves volatility forecasting.
Pieterjelle van der Sluis (Haarlem, 1970) graduated from the Free University
Amsterdam in 1994 with a degree in Econometrics. He then became a PhD student at the Tinbergen Institute and an Assistant Researcher at the former Department of Actuarial Science and Econometrics at the University of Amsterdam. His research work has been published in several refereed international journals and has also been presented at many major international conferences. Since 1998 he is affiliated to Tilburg University, both as an Assistant Professor of Econometrics, Quantitative Finance and Statistics at the Department of Econometrics, and as a Fellow of CentER. Pieter Jelle's current research interests are in Financial Econometrics and the Pricing of Derivatives.
