This paper has been announced in the following NEP Reports:

• NEP-ALL-2006-11-25 (All new papers)
• NEP-ETS-2006-11-25 (Econometric Time Series)

1. L. Bauwens & C.S. Bos & H.K. van Dijk, 1999. "Adaptive Polar Sampling with an application to a Bayes measure of Value-at-Risk," Econometric Institute Report 167, Erasmus University Rotterdam, Econometric Institute. [Downloadable!]
   Other versions:
   • Luc Bauwens & Charles S. Bos & Herman K. van Dijk, 1999. "Adaptive Polar Sampling with an Application to a Bayes Measure of Value-at-Risk," Tinbergen Institute Discussion Papers 99-082/4, Tinbergen Institute. [Downloadable!]
   • BAUWENS, Luc & BOS, Charles S. & VAN DIJK, Herman K., 1999. "Adaptive polar sampling with an application to a Bayes measure of value-at-risk," CORE Discussion Papers 1999057, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE). [Downloadable!]
   • Bauwens, L. & Bos, C.S. & Dijk, H.K. van, 1999. "Adaptive Polar Sampling with an Application to a Bayes Measure of Value-at-Risk," Econometric Institute Report TI 99-082/4 Revision_Date, Erasmus University Rotterdam, Econometric Institute. [Downloadable!]
   • K. Van Dijk & Luc Bauwens & Charles Bos, 2000. "Adaptive Polar Sampling With An Application To A Bayes Measure Of Value-At-Risk," Computing in Economics and Finance 2000 145, Society for Computational Economics.
2. Markku Lanne & Pentti Saikkonen, 2003. "Modeling the U.S. Short-Term Interest Rate by Mixture Autoregressive Processes," Journal of Financial Econometrics, Oxford University Press, vol. 1(1), pages 96-125.
   Other versions:
   • M. Lanne & P. Saikkonen, . "Modeling the U.S. Short-Term Interest Rate by Mixture Autoregressive Processes," Sonderforschungsbereich 373 2000-76, Humboldt Universitaet Berlin.
   • Markku Lanne & Pentti Saikkonen, 2001. "Modeling the U.S. Short-Term Interest Rate by Mixture Autoregressive Processes," CeNDEF Workshop Papers, January 2001 PO5, Universiteit van Amsterdam, Center for Nonlinear Dynamics in Economics and Finance.
3. Luc Bauwens & Charles S. Bos & Herman K. van Dijk & Rutger D. van Oest, 2002. "Adaptive Polar Sampling," Computing in Economics and Finance 2002 307, Society for Computational Economics.
4. Lamoureux, Christopher G & Lastrapes, William D, 1990. " Heteroskedasticity in Stock Return Data: Volume versus GARCH Effects," Journal of Finance, American Finance Association, vol. 45(1), pages 221-29, March. [Downloadable!] (restricted)
5. Markus Haas, 2004. "Mixed Normal Conditional Heteroskedasticity," Journal of Financial Econometrics, Oxford University Press, vol. 2(2), pages 211-250. [Downloadable!] (restricted)
6. Vlaar, Peter J G & Palm, Franz C, 1993. "The Message in Weekly Exchange Rates in the European Monetary System: Mean Reversion, Conditional Heteroscedasticity, and Jumps," Journal of Business & Economic Statistics, American Statistical Association, vol. 11(3), pages 351-60, July.
7. Schwert, G William, 1989. " Why Does Stock Market Volatility Change over Time?," Journal of Finance, American Finance Association, vol. 44(5), pages 1115-53, December. [Downloadable!] (restricted)
   Other versions:
   • G. William Schwert, 1990. "Why Does Stock Market Volatility Change Over Time?," NBER Working Papers 2798, National Bureau of Economic Research, Inc. [Downloadable!] (restricted)
8. Bollen, Nicolas P. B. & Gray, Stephen F. & Whaley, Robert E., 2000. "Regime switching in foreign exchange rates: Evidence from currency option prices," Journal of Econometrics, Elsevier, vol. 94(1-2), pages 239-276. [Downloadable!] (restricted)
9. Thomas Mikosch & Catalin Starica, 2004. "Non-stationarities in financial time series, the long range dependence and the IGARCH effects," Econometrics 0412005, EconWPA. [Downloadable!]
10. Dueker, Michael J, 1997. "Markov Switching in GARCH Processes and Mean-Reverting Stock-Market Volatility," Journal of Business & Economic Statistics, American Statistical Association, vol. 15(1), pages 26-34, January.
    Other versions:
    • Michael Dueker, 1995. "Markov switching in GARCH processes and mean reverting stock market volatility," Working Papers 1994-015, Federal Reserve Bank of St. Louis. [Downloadable!]
11. Hansen, Bruce E, 1994. "Autoregressive Conditional Density Estimation," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 35(3), pages 705-30, August. [Downloadable!] (restricted)
    Other versions:
    • Hansen, B.E., 1992. "Autoregressive Conditional Density Estimation," RCER Working Papers 322, University of Rochester - Center for Economic Research (RCER).
12. Klaassen, F., 1998. "Improving garch volatility forecasts," Discussion Paper 52, Tilburg University, Center for Economic Research. [Downloadable!]
13. Gray, Stephen F., 1996. "Modeling the conditional distribution of interest rates as a regime-switching process," Journal of Financial Economics, Elsevier, vol. 42(1), pages 27-62, September. [Downloadable!] (restricted)
14. Chris Brooks, 2005. "Autoregressive Conditional Kurtosis," Journal of Financial Econometrics, Oxford University Press, vol. 3(3), pages 399-421. [Downloadable!] (restricted)
    Other versions:
    • Chris Brooks & Simon P. Burke & Gita Persand, 2002. "Augoregressive Conditional Kurtosis," ICMA Centre Discussion Papers in Finance icma-dp2002-05, Henley Business School, Reading University. [Downloadable!]
15. Kim, Chang-Jin, 1994. "Dynamic linear models with Markov-switching," Journal of Econometrics, Elsevier, vol. 60(1-2), pages 1-22. [Downloadable!] (restricted)
16. Kai-Li Wang & Christopher Fawson & Christopher B. Barrett & James B. McDonald, 2001. "A flexible parametric GARCH model with an application to exchange rates," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 16(4), pages 521-536. [Downloadable!]
    Other versions:
    • Wang, Kai Li & Fawson, Christopher & Barrett, Christopher B. & McDonald, James B., 1998. "A Flexible Parametric Garch Model With An Application To Exchange Rates," Economics Research Institute, ERI Study Papers 28355, Utah State University, Economics Department. [Downloadable!]
17. Tim Bollerslev & Jeffrey Wooldridge, 1992. "Quasi-maximum likelihood estimation and inference in dynamic models with time-varying covariances," Econometric Reviews, Taylor and Francis Journals, vol. 11(2), pages 143-172. [Downloadable!] (restricted)
18. BAUWENS, Luc & ROMBOUTS, Jeroen V.K., 2005. "Bayesian inference for the mixed conditional heteroskedasticity model," CORE Discussion Papers 2005085, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE). [Downloadable!]
    Other versions:
    • Luc, Bauwens & J.V.K., ROMBOUTS, 2005. "Bayesian inference for the mixed conditional heteroskedasticity model," Discussion Papers (ECON - Département des Sciences Economiques) 2005058, Université catholique de Louvain, Département des Sciences Economiques. [Downloadable!]
    • Luc Bauwens & Jeroen V.K. Rombouts, 2006. "Bayesian inference for the mixed conditional heteroskedasticity model," Cahiers de recherche 06-07, HEC Montréal, Institut d'économie appliquée. [Downloadable!]
    • L. Bauwens & J.V.K. Rombouts, 2007. "Bayesian inference for the mixed conditional heteroskedasticity model," Econometrics Journal, Royal Economic Society, vol. 10(2), pages 408-425, 07. [Downloadable!] (restricted)
19. Hamilton, James D. & Susmel, Raul, 1994. "Autoregressive conditional heteroskedasticity and changes in regime," Journal of Econometrics, Elsevier, vol. 64(1-2), pages 307-333. [Downloadable!] (restricted)
    Other versions:
    • James D. Hamilton & Raul Susmel, 1993. "Autoregressive Conditional Heteroskedasticity and Changes in Regime," University of California at San Diego, Economics Working Paper Series 93-28, Department of Economics, UC San Diego.
20. Bollerslev, Tim, 1986. "Generalized autoregressive conditional heteroskedasticity," Journal of Econometrics, Elsevier, vol. 31(3), pages 307-327, April. [Downloadable!] (restricted)
21. Franc Klaassen, 2002. "Improving GARCH volatility forecasts with regime-switching GARCH," Empirical Economics, Springer, vol. 27(2), pages 363-394. [Downloadable!] (restricted)
22. Thomas Mikosch & Cătălin Stărică, 2004. "Nonstationarities in Financial Time Series, the Long-Range Dependence, and the IGARCH Effects," The Review of Economics and Statistics, MIT Press, vol. 86(1), pages 378-390, 01. [Downloadable!] (restricted)
23. Christian Francq & Michel Roussignol & Jean-Michel Zakoian, . "Conditional heteroskedasticity driven by hidden Markov chains," Sonderforschungsbereich 373 1998-86, Humboldt Universitaet Berlin.
    Other versions:
    • Christian Francq ; Michel Roussignol ; Jean-Michel Zakoïan, . "Conditional Heteroskedasticity Driven by Hidden Markov Chains," Working Papers 98-45, Centre de Recherche en Economie et Statistique. [Downloadable!]

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. Luc, BAUWENS & G., STORTI, 2007. "A Component GARCH Model with Time Varying Weights," Discussion Papers (ECON - Département des Sciences Economiques) 2007012, Université catholique de Louvain, Département des Sciences Economiques. [Downloadable!]
   Other versions:
   • BAUWENS, Luc & STORTI, Giuseppe, 2007. "A component GARCH model with time varying weights," CORE Discussion Papers 2007019, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE). [Downloadable!]
   • Giuseppe Storti & Luc Bauwens, 2006. "A component GARCH model with time varying weights," Computing in Economics and Finance 2006 388, Society for Computational Economics.
   • Luc Bauwens & Giuseppe Storti, 2009. "A Component GARCH Model with Time Varying Weights," Studies in Nonlinear Dynamics & Econometrics, Berkeley Electronic Press, vol. 13(2). [Downloadable!]
2. Chun Liu & John M Maheu, 2007. "Are there Structural Breaks in Realized Volatility?," Working Papers tecipa-304, University of Toronto, Department of Economics. [Downloadable!]
   Other versions:
   • Chun Liu & John M. Maheu, 2008. "Are There Structural Breaks in Realized Volatility?," Journal of Financial Econometrics, Oxford University Press, vol. 6(3), pages 326-360, Summer. [Downloadable!] (restricted)
3. Luc, BAUWENS & Nikolaus, HAUTSCH, 2006. "Modelling Financial High Frequency Data Using Point Processes," Discussion Papers (ECON - Département des Sciences Economiques) 2006039, Université catholique de Louvain, Département des Sciences Economiques. [Downloadable!]
   Other versions:
   • Luc Bauwens & Nikolaus Hautsch, 2007. "Modelling Financial High Frequency Data Using Point Processes," SFB 649 Discussion Papers SFB649DP2007-066, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany. [Downloadable!]
   • BAUWENS, Luc & HAUTSCH, Nikolaus, 2006. "Modelling financial high frequency data using point processes," CORE Discussion Papers 2006080, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE). [Downloadable!]
4. Lanne, Markku & Luoto, Jani, 2007. "Robustness of the Risk-Return Relationship in the U.S. Stock Market," MPRA Paper 3879, University Library of Munich, Germany. [Downloadable!]
   Other versions:
   • Lanne, Markku & Luoto, Jani, 2008. "Robustness of the risk-return relationship in the U.S. stock market," Finance Research Letters, Elsevier, vol. 5(2), pages 118-127, June. [Downloadable!] (restricted)
5. Zhongfang He & John M Maheu, 2008. "Real Time Detection of Structural Breaks in GARCH Models," Working Papers tecipa-336, University of Toronto, Department of Economics. [Downloadable!]
   Other versions:
   • Zhongfang He & John M. Maheu, 2009. "Real Time Detection of Structural Breaks in GARCH Models," Working Paper Series 11-09, Rimini Centre for Economic Analysis, revised Jan 2009. [Downloadable!]