This file is part of IDEAS, which uses RePEc data


[ Papers | Articles | Software | Books | Chapters | Authors | Institutions | JEL Classification | NEP reports | Search | New papers by email | Author registration | Rankings | Volunteers | FAQ | Blog | Help! ]

Adaptive Polar Sampling with an application to a Bayes measure of Value-at-Risk

Author info | Abstract | Publisher info | Download info | Related research | Statistics
Author Info
L. Bauwens
C.S. Bos ()
H.K. van Dijk () (FEW-Econometrie en besliskunde)

Additional information is available for the following registered author(s):

Abstract

Adaptive Polar Sampling (APS) is proposed as a Markov chain Monte Carlo method for Bayesian analysis of models with ill-behaved posterior distributions. In order to sample efficiently from such a distribution, a location-scale transformation and a transformation to polar coordinates are used. After the transformation to polar coordinates, a Metropolis-Hastings algorithm is applied to sample directions and, conditionally on these, distances are generated by inverting the CDF. A sequential procedure is applied to update the location and scale. Tested on a set of canonical models that feature near non-identifiability, strong correlation, and bimodality, APS compares favourably with the standard Metropolis-Hastings sampler in terms of parsimony and robustness. APS is applied within a Bayesian analysis of a GARCH-mixture model which is used for the evaluation of the Value-at-Risk of the return of the Dow Jones stock index.

Download Info
To download:

If you experience problems downloading a file, check if you have the proper application to view it first. Information about this may be contained in the File-Format links below. In case of further problems read the IDEAS help page. Note that these files are not on the IDEAS site. Please be patient as the files may be large.

File URL: http://www.eur.nl/WebDOC/doc/econometrie/feweco19991109152552.pdf
File Format: application/pdf
File Function:
Download Restriction: no

Publisher Info
Paper provided by Erasmus University Rotterdam, Econometric Institute in its series Econometric Institute Report with number 167.

Download reference. The following formats are available: HTML (with abstract), plain text (with abstract), BibTeX, RIS (EndNote, RefMan, ProCite), ReDIF
Length:
Date of creation: 1999
Date of revision:
Handle: RePEc:dgr:eureir:1999167

Contact details of provider:
Web page: http://www.few.eur.nl/few

For technical questions regarding this item, or to correct its listing, contact: (Anneke Kop).

Related research
Keywords: Markov chain Monte Carlo simulation polar coordinates GARCH ill-behaved posterior;

Other versions of this item:

Find related papers by JEL classification:
C11 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: General - - - Bayesian Analysis
C15 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: General - - - Statistical Simulation Methods
C63 - Mathematical and Quantitative Methods - - Mathematical Methods and Programming - - - Computational Techniques

This paper has been announced in the following NEP Reports:

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.:
  1. van Dijk, H. K. & Kloek, T., 1980. "Further experience in Bayesian analysis using Monte Carlo integration," Journal of Econometrics, Elsevier, vol. 14(3), pages 307-328, December. [Downloadable!] (restricted)
  2. John Geweke, 1998. "Using simulation methods for Bayesian econometric models: inference, development, and communication," Staff Report 249, Federal Reserve Bank of Minneapolis. [Downloadable!]
    Other versions:
  3. Richard Paap & Herman K. van Dijk, 1999. "Bayes Estimates of Markov Trends in Possibly Cointegrated Series: An Application to US Consumption and Income," Tinbergen Institute Discussion Papers 99-024/4, Tinbergen Institute. [Downloadable!]
    Other versions:
  4. Kleibergen, F & Van Dijk, H K, 1993. "Non-stationarity in GARCH Models: A Bayesian Analysis," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 8(S), pages S41-61, Suppl. De. [Downloadable!] (restricted)
    Other versions:
  5. Kleibergen, Frank & van Dijk, Herman K., 1998. "Bayesian Simultaneous Equations Analysis Using Reduced Rank Structures," Econometric Theory, Cambridge University Press, vol. 14(06), pages 701-743, December. [Downloadable!]
    Other versions:
  6. repec:cup:etheor:v:10:y:1994:i:3-4:p:514-51 is not listed on IDEAS
  7. Kleibergen, Frank & van Dijk, Herman K., 1994. "On the Shape of the Likelihood/Posterior in Cointegration Models," Econometric Theory, Cambridge University Press, vol. 10(3-4), pages 514-551, August. [Downloadable!]
    Other versions:
  8. Albert, James H & Chib, Siddhartha, 1993. "Bayes Inference via Gibbs Sampling of Autoregressive Time Series Subject to Markov Mean and Variance Shifts," Journal of Business & Economic Statistics, American Statistical Association, vol. 11(1), pages 1-15, January.
  9. Luc Bauwens & Michel Lubrano, 1998. "Bayesian inference on GARCH models using the Gibbs sampler," Econometrics Journal, Royal Economic Society, vol. 1(Conferenc), pages C23-C46.
    Other versions:
  10. John Geweke, 1991. "Evaluating the accuracy of sampling-based approaches to the calculation of posterior moments," Staff Report 148, Federal Reserve Bank of Minneapolis. [Downloadable!]
  11. Frank Kleibergen & Herman K. van Dijk, 1998. "Bayesian Simultaneous Equations Analysis using Reduced Rank Structures," Tinbergen Institute Discussion Papers 98-025/4, Tinbergen Institute. [Downloadable!]
  12. Van Dijk, Herman K. & Kloek, Teun & Boender, C. Guus E., 1985. "Posterior moments computed by mixed integration," Journal of Econometrics, Elsevier, vol. 29(1-2), pages 3-18. [Downloadable!] (restricted)
  13. Chib, Siddhartha & Greenberg, Edward, 1996. "Markov Chain Monte Carlo Simulation Methods in Econometrics," Econometric Theory, Cambridge University Press, vol. 12(03), pages 409-431, August. [Downloadable!]
  14. Geweke, John, 1989. "Exact predictive densities for linear models with arch disturbances," Journal of Econometrics, Elsevier, vol. 40(1), pages 63-86, January. [Downloadable!] (restricted)
  15. G. Koop & H.K. van Dijk, 1999. "Testing for integration using evolving trend and seasonal models A Bayesian approach," Econometric Institute Report 163, Erasmus University Rotterdam, Econometric Institute. [Downloadable!]
    Other versions:
  16. repec:cup:etheor:v:12:y:1996:i:3:p:409-31 is not listed on IDEAS
  17. Kim, Sangjoon & Shephard, Neil & Chib, Siddhartha, 1998. "Stochastic Volatility: Likelihood Inference and Comparison with ARCH Models," Review of Economic Studies, Blackwell Publishing, vol. 65(3), pages 361-93, July. [Downloadable!] (restricted)
    Other versions:
  18. Geweke, J, 1993. "Bayesian Treatment of the Independent Student- t Linear Model," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 8(S), pages S19-40, Suppl. De. [Downloadable!] (restricted)
  19. Jacquier, Eric & Polson, Nicholas G & Rossi, Peter E, 1994. "Bayesian Analysis of Stochastic Volatility Models," Journal of Business & Economic Statistics, American Statistical Association, vol. 12(4), pages 371-89, October.
    Other versions:
Full references

Cited by:
(explanations, 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.)

  1. L. Bauwens & C.S. Bos & H.K. Van Dijk & R.D. Van Oest, 2002. "Adaptive polar sampling, a class of flexibel and robust Monte Carlo integration methods," Econometric Institute Report 278, Erasmus University Rotterdam, Econometric Institute. [Downloadable!]
    Other versions:
  2. C.S. Bos & R.J. Mahieu & H.K. Van Dijk, 2000. "On the variation of hedging decisions in daily currency risk management," Econometric Institute Report 206, Erasmus University Rotterdam, Econometric Institute. [Downloadable!]
    Other versions:
  3. Markus Haas & Stefan Mittnik & Marc S. Paolella, 2006. "Multivariate Normal Mixture GARCH," CFS Working Paper Series 2006/09, Center for Financial Studies. [Downloadable!]
  4. Luc, BAUWENS & Arie, PREMINGER & Jeroen, ROMBOUTS, 2006. "Regime switching GARCH models," Discussion Papers (ECON - Département des Sciences Economiques) 2006006, Université catholique de Louvain, Département des Sciences Economiques. [Downloadable!]
    Other versions:
  5. Dinghai Xu & Tony S. Wirjanto, 2008. "An Empirical Characteristic Function Approach to VaR under a Mixture of Normal Distribution with Time-Varying Volatility," Working Papers 08008, University of Waterloo, Department of Economics. [Downloadable!]
  6. Emese Lazar & Carol Alexander, 2006. "Normal mixture GARCH(1,1): applications to exchange rate modelling," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 21(3), pages 307-336. [Downloadable!]
Statistics
Access and download statistics

Did you know? RePEc and its associated services are free for contributors and users, and do not accept any advertising.

This page was last updated on 2009-11-25.

This information is provided to you by IDEAS at the Department of Economics, College of Liberal Arts and Sciences, University of Connecticut using RePEc data on a server sponsored by the Society for Economic Dynamics.