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.Download Info
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Paper provided by Economics Group, Nuffield College, University of Oxford in its series Economics Papers with number 2004-W02.Length: 30 pages
Date of creation: 25 Feb 2004
Date of revision:
Handle: RePEc:nuf:econwp:042
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Web page: http://www.nuff.ox.ac.uk/economics/
Related research
Keywords: Markov chain Monte Carlo; particle filter; cubic spline; state space form; stochastic volatility.;Other versions of this item:
- Charles Bos & Neil Shephard, 2006. "Inference for Adaptive Time Series Models: Stochastic Volatility and Conditionally Gaussian State Space Form," Econometric Reviews, Taylor and Francis Journals, vol. 25(2-3), pages 219-244.
- C15 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Statistical Simulation Methods: General
- C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models
- C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation
- F31 - International Economics - - International Finance - - - Foreign Exchange
This paper has been announced in the following NEP Reports:
- NEP-ALL-2004-02-29 (All new papers)
- NEP-ECM-2004-03-03 (Econometrics)
- NEP-ETS-2004-02-29 (Econometric Time Series)
References
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Citations
Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.Cited by:
- Chris M Strickland & Gael Martin & Catherine S Forbes, 2006.
"Parameterisation and Efficient MCMC Estimation of Non-Gaussian State Space Models,"
Monash Econometrics and Business Statistics Working Papers
22/06, Monash University, Department of Econometrics and Business Statistics.
- Strickland, Chris M. & Martin, Gael M. & Forbes, Catherine S., 2008. "Parameterisation and efficient MCMC estimation of non-Gaussian state space models," Computational Statistics & Data Analysis, Elsevier, vol. 52(6), pages 2911-2930, February.
- Neil Shephard, 2013. "Martingale unobserved component models," Economics Papers 2013-W01, Economics Group, Nuffield College, University of Oxford.
- Michel Beine & Charles S. Bos & Sebastian Laurent, 2005. "The Impact of Central Bank FX Interventions on Currency Components," Tinbergen Institute Discussion Papers 05-103/4, Tinbergen Institute.
- Charles S. Bos, 2008. "Model-based Estimation of High Frequency Jump Diffusions with Microstructure Noise and Stochastic Volatility," Tinbergen Institute Discussion Papers 08-011/4, Tinbergen Institute.
- Carmen Broto & Esther Ruiz, 2008.
"Testing for conditional heteroscedasticity in the components of inflation,"
Banco de España Working Papers
0812, Banco de España.
- Carmen Broto & Esther Ruiz, 2009. "Testing for Conditional Heteroscedasticity in the Components of Inflation," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 13(2), pages 4.
- Broto, Carmen & Ruiz, Esther, 2009. "Testing for conditional heteroscedasticity in the components of inflation," Open Access publications from Universidad Carlos III de Madrid info:hdl:10016/9023, Universidad Carlos III de Madrid.
- Creal, D., 2009. "A survey of sequential Monte Carlo methods for economics and finance," Serie Research Memoranda 0018, VU University Amsterdam, Faculty of Economics, Business Administration and Econometrics.
- Strickland, Chris M. & Turner, Ian. W. & Denham, Robert & Mengersen, Kerrie L., 2009. "Efficient Bayesian estimation of multivariate state space models," Computational Statistics & Data Analysis, Elsevier, vol. 53(12), pages 4116-4125, October.
- Neil Shephard, 2013. "Martingale unobserved component models," Economics Series Working Papers 644, University of Oxford, Department of Economics.
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