Estimating Stochastic Volatility Models: A Comparison of Two Importance Samplers

Verfasser / Beitragende:
[Kai Ming Lee, Siem Jan Koopman]
Ort, Verlag, Jahr:
2004
Enthalten in:
Studies in Nonlinear Dynamics & Econometrics, 8/2(2004-05-18)
Format:
Artikel (online)
ID: 378929763
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024 7 0 |a 10.2202/1558-3708.1210  |2 doi 
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245 0 0 |a Estimating Stochastic Volatility Models: A Comparison of Two Importance Samplers  |h [Elektronische Daten]  |c [Kai Ming Lee, Siem Jan Koopman] 
520 3 |a In this paper, we describe and compare two simulated Maximum Likelihood estimation methods for a basic stochastic volatility model. For both methods, the likelihood function is estimated using importance sampling techniques. Based on a Monte Carlo study, we assess which method is more effective. Further, we validate the two methods using diagnostic importance sampling test procedures. Stochastic volatility models with Gaussian and Student-t distributed disturbances are considered. 
540 |a ©2011 Walter de Gruyter GmbH & Co. KG, Berlin/Boston 
700 1 |a Lee  |D Kai Ming  |u Free University Amsterdam and Tinbergen Institute, klee@feweb.vu.nl  |4 aut 
700 1 |a Koopman  |D Siem Jan  |u Free University Amsterdam, s.j.koopman@feweb.vu.nl  |4 aut 
773 0 |t Studies in Nonlinear Dynamics & Econometrics  |d De Gruyter  |g 8/2(2004-05-18)  |q 8:2  |1 2004  |2 8  |o snde 
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950 |B NATIONALLICENCE  |P 700  |E 1-  |a Lee  |D Kai Ming  |u Free University Amsterdam and Tinbergen Institute, klee@feweb.vu.nl  |4 aut 
950 |B NATIONALLICENCE  |P 700  |E 1-  |a Koopman  |D Siem Jan  |u Free University Amsterdam, s.j.koopman@feweb.vu.nl  |4 aut 
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