Estimation of Stochastic Volatility Models with Heavy Tails and Serial Dependence
Financial time series often exhibit properties that depart from the usual assumptions of serial independence and normality. These include volatility clustering, heavy-tailedness and serial dependence. A voluminous literature on different approaches for modeling these empirical regularities has emerged in the last decade. In this paper we review the estimation of a variety of highly flexible stochastic volatility models, and introduce some efficient algorithms based on recent advances in state space simulation techniques. These estimation methods are illustrated via empirical examples involving precious metal and foreign exchange returns. The corresponding Matlab code is also provided.
|Date of creation:||Nov 2013|
|Date of revision:|
|Contact details of provider:|| Postal: Crawford Building, Lennox Crossing, Building #132, Canberra ACT 2601|
Phone: +61 2 6125 4705
Fax: +61 2 6125 5448
Web page: http://cama.crawford.anu.edu.au
More information through EDIRC
References listed on IDEAS
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
- Koop,Gary & Poirier,Dale J. & Tobias,Justin L., 2007.
"Bayesian Econometric Methods,"
Cambridge University Press, number 9780521671736, November.
- Joshua C C Chan, 2012.
"Moving Average Stochastic Volatility Models with Application to Inflation Forecast,"
ANU Working Papers in Economics and Econometrics
2012-591, Australian National University, College of Business and Economics, School of Economics.
- Chan, Joshua C.C., 2013. "Moving average stochastic volatility models with application to inflation forecast," Journal of Econometrics, Elsevier, vol. 176(2), pages 162-172.
- Joshua C.C. Chan, 2013. "Moving Average Stochastic Volatility Models with Application to Inflation Forecast," CAMA Working Papers 2013-31, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
- Joshua C C Chan & Gary Koop & Roberto Leon-Gonzales & Rodney W Strachan, 2011.
"Time Varying Dimension Models,"
CAMA Working Papers
2011-28, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
- Joshua C.C. Chan & Gary Koop & Roberto Leon-Gonzalez & Rodney W. Strachan, 2010. "Time Varying Dimension Models," Working Paper Series 44_10, The Rimini Centre for Economic Analysis.
- Chan, Joshua C C & Koop, Gary & Leon-Gonzalez, Roberto & Strachan, Rodney W, 2010. "Time Varying Dimension Models," SIRE Discussion Papers 2012-33, Scottish Institute for Research in Economics (SIRE).
- Joshua Chan & Gary Koop & Roberto Leon-Gonzalez & Rodney Strachan, 2011. "Time Varying Dimension Models," Working Papers 1116, University of Strathclyde Business School, Department of Economics.
- Joshua C.C. Chan & Garry Koop & Roberto Leon Gonzales & Rodney W. Strachan, 2010. "Time Varying Dimension Models," ANU Working Papers in Economics and Econometrics 2010-523, Australian National University, College of Business and Economics, School of Economics.
- McCausland, William J. & Miller, Shirley & Pelletier, Denis, 2011. "Simulation smoothing for state-space models: A computational efficiency analysis," Computational Statistics & Data Analysis, Elsevier, vol. 55(1), pages 199-212, January.
- Ivan Jeliazkov & Rui Liu, 2010. "A model-based ranking of U.S. recessions," Economics Bulletin, AccessEcon, vol. 30(3), pages 2289-2296.
- Wang, Joanna J.J. & Chan, Jennifer S.K. & Choy, S.T. Boris, 2011. "Stochastic volatility models with leverage and heavy-tailed distributions: A Bayesian approach using scale mixtures," Computational Statistics & Data Analysis, Elsevier, vol. 55(1), pages 852-862, January.
- Sangjoon Kim & Neil Shephard & Siddhartha Chib, 1998. "Stochastic Volatility: Likelihood Inference and Comparison with ARCH Models," Review of Economic Studies, Oxford University Press, vol. 65(3), pages 361-393.
When requesting a correction, please mention this item's handle: RePEc:een:camaaa:2013-74. See general information about how to correct material in RePEc.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Cama Admin)
If references are entirely missing, you can add them using this form.