Working paper icon

Working paper

Inference for Adaptive Time Series Models: Stochastic Volatility and Conditionally Gaussian State Space Form.

Abstract:
In this paper we replace the Gaussian errors in the standard Gaussian, linear state space model with stochastic volatility processes. This is called a GSSF-SV model. We show that conventional MCMC algoritms for this type of model are ineffective, but that this problem can be removed by reparameterising the model. We illustrate our results on an example from financial economics and one from the nonparametric regression literature. We also develop an effective particle filter for this model which is useful to assess the fit of the model.

Actions


Access Document


Files:
Publisher:
Nuffield College (University of Oxford)
Host title:
Economics Group, Nuffield College, University of Oxford, Economics Papers
Series:
Economics Group, Nuffield College, University of Oxford, Economics Papers
Publication date:
2004-01-01
Language:
English
UUID:
uuid:e8eec2bf-28c6-4e09-95ff-3a8369e261b9
Local pid:
oai:economics.ouls.ox.ac.uk:11892
Deposit date:
2011-08-16

Terms of use


Views and Downloads






If you are the owner of this record, you can report an update to it here: Report update to this record

TO TOP