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Adaptive Polar Sampling with an Application to a Bayes Measure of Value-at-Risk

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Author Info
Bauwens, L.
Bos, C.S.
Van Dijk, H.K.

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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 efficiency from such a distribution, location-scale transformation and a transformation to polar coordinates are used.

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Publisher Info
Paper provided by Catholique de Louvain - Center for Operations Research and Economics in its series Papers with number 9957.

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Length: 28 pages
Date of creation: 1999
Date of revision:
Handle: RePEc:fth:louvco:9957

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Postal: BELGIQUE, UNIVERSITE CATHOLIQUE DE LOUVAIN, CENTER FOR OPERATIONS RESEARCH AND ECONOMETRICS (CORE), LOUVAIN-LA-NEUVE, BELGIQUE.
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Related research
Keywords: ECONOMETRICS MATHEMATICAL ANALYSIS SIMULATION

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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

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. 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:
  2. 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:
  3. repec:cup:etheor:v:10:y:1994:i:3-4:p:514-51 is not listed on IDEAS
  4. 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.
  5. 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.
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  6. 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!]
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  7. Kleibergen, F.R. & Van Dijk, H.K., 1993. "On the Shape of the Likelyhood/Posterior in Cointegration Models," Papers 9315-a, Erasmus University of Rotterdam - Econometric Institute.
  8. 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)
  9. 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)
  10. 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!]
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  11. repec:cup:etheor:v:12:y:1996:i:3:p:409-31 is not listed on IDEAS
  12. 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)
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  13. 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)
  14. 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.
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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. Markus Haas & Stefan Mittnik & Marc S. Paolella, 2006. "Multivariate Normal Mixture GARCH," CFS Working Paper Series 2006/09, Center for Financial Studies. [Downloadable!]
  2. Charles S. Bos & Ronald J. Mahieu & Herman K. van Dijk, 2001. "On the Variation of Hedging Decisions in Daily Currency Risk Management," Tinbergen Institute Discussion Papers 01-018/4, Tinbergen Institute. [Downloadable!]
    Other versions:
  3. 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!]
  4. 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!]
  5. Luc, BAUWENS & Arie, PREMINGER & Jeroen, ROMBOUTS, 2006. "Regime switching GARCH models," Université catholique de Louvain, Département des Sciences Economiques Working Paper 2006006, Université catholique de Louvain, Département des Sciences Economiques. [Downloadable!]
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