Mixed Exponential Power Asymmetric Conditional Heteroskedasticity
To match the stylized facts of high frequency financial time series precisely and parsimoniously, this paper presents a finite mixture of conditional exponential power distributions where each component exhibits asymmetric conditional heteroskedasticity. We provide stationarity conditions and unconditional moments to the fourth order. We apply this new class to Dow Jones index returns. We find that a two-component mixed exponential power distribution dominates mixed normal distributions with more components, and more parameters, both in-sample and out-of-sample. In contrast to mixed normal distributions, all the conditional variance processes become stationary. This happens because the mixed exponential power distribution allows for component-specific shape parameters so that it can better capture the tail behaviour. Therefore, the more general new class has attractive features over mixed normal distributions in our application: Less components are necessary and the conditional variances in the components are stationary processes. Results on NASDAQ index returns are similar.
|Date of creation:||Dec 2007|
|Date of revision:|
|Contact details of provider:|| Postal: |
Phone: (514) 340-6463
Fax: (514) 340-6469
Web page: http://www.hec.ca/iea/
More information through EDIRC
|Order Information:|| Postal: Institut d'économie appliquée HEC Montréal 3000, Chemin de la Côte-Sainte-Catherine Montréal, Québec H3T 2A7|
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.:
- Roman Liesenfeld & Robert C. Jung, 2000.
"Stochastic volatility models: conditional normality versus heavy-tailed distributions,"
Journal of Applied Econometrics,
John Wiley & Sons, Ltd., vol. 15(2), pages 137-160.
- Liesenfeld, Roman & Jung, Robert C., 1997. "Stochastic volatility models: Conditional normality versus heavy tailed distributions," Tübinger Diskussionsbeiträge 103, University of Tübingen, School of Business and Economics.
- Chris Brooks, 2005.
"Autoregressive Conditional Kurtosis,"
Journal of Financial Econometrics,
Society for Financial Econometrics, vol. 3(3), pages 399-421.
- Bauwens, L. & Hafner, C.M. & Rombouts, J.V.K., 2007.
"Multivariate mixed normal conditional heteroskedasticity,"
Computational Statistics & Data Analysis,
Elsevier, vol. 51(7), pages 3551-3566, April.
- BAUWENS, Luc & HAFNER, Christian M. & ROMBOUTS, Jeroen VK, . "Multivariate mixed normal conditional heteroskedasticity," CORE Discussion Papers RP -1906, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
- Luc, BAUWENS & C.M., HAFNER & J.V.K., ROMBOUTS, 2006. "Multivariate mixed normal conditional heteroskedasticity," Discussion Papers (ECON - Département des Sciences Economiques) 2006007, Université catholique de Louvain, Département des Sciences Economiques.
- BAUWENS, Luc & HAFNER, Christian & ROMBOUTS, Jeroen, 2006. "Multivariate mixed normal conditional heteroskedasticity," CORE Discussion Papers 2006012, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
- 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.
- Frühwirth-Schnatter, Sylvia & Kaufmann, Sylvia, 2004.
"Model-based Clustering of Multiple Time Series,"
CEPR Discussion Papers
4650, C.E.P.R. Discussion Papers.
- Glosten, Lawrence R & Jagannathan, Ravi & Runkle, David E, 1993.
" On the Relation between the Expected Value and the Volatility of the Nominal Excess Return on Stocks,"
Journal of Finance,
American Finance Association, vol. 48(5), pages 1779-1801, December.
- Lawrence R. Glosten & Ravi Jagannathan & David E. Runkle, 1993. "On the relation between the expected value and the volatility of the nominal excess return on stocks," Staff Report 157, Federal Reserve Bank of Minneapolis.
- Robert F. Engle & Victor K. Ng, 1991.
"Measuring and Testing the Impact of News on Volatility,"
NBER Working Papers
3681, National Bureau of Economic Research, Inc.
- Engle, Robert F & Ng, Victor K, 1993. " Measuring and Testing the Impact of News on Volatility," Journal of Finance, American Finance Association, vol. 48(5), pages 1749-78, December.
- Ivana Komunjer, 2004.
"Asymmetric Power Distribution: Theory and Applications to Risk Measurement,"
Econometric Society 2004 Latin American Meetings
44, Econometric Society.
- Ivana Komunjer, 2007. "Asymmetric power distribution: Theory and applications to risk measurement," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 22(5), pages 891-921.
- Nelson, Daniel B, 1991. "Conditional Heteroskedasticity in Asset Returns: A New Approach," Econometrica, Econometric Society, vol. 59(2), pages 347-70, March.
- Tucker, Alan L & Pond, Lallon, 1988. "The Probability Distribution of Foreign Exchange Price Changes: Tests of Candidate Processes," The Review of Economics and Statistics, MIT Press, vol. 70(4), pages 638-47, November.
- Harvey, Campbell R. & Siddique, Akhtar, 1999. "Autoregressive Conditional Skewness," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 34(04), pages 465-487, December.
- 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.
- Mittnik, Stefan & Paolella, Marc S. & Rachev, Svetlozar T., 2002. "Stationarity of stable power-GARCH processes," Journal of Econometrics, Elsevier, vol. 106(1), pages 97-107, January.
- Markus Haas, 2004.
"Mixed Normal Conditional Heteroskedasticity,"
Journal of Financial Econometrics,
Society for Financial Econometrics, vol. 2(2), pages 211-250.
- 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, February.
- Thomas Mikosch & Catalin Starica, 2004. "Non-stationarities in financial time series, the long range dependence and the IGARCH effects," Econometrics 0412005, EconWPA.
- Gikas A. Hardouvelis & Panayiotis Theodossiou, 2002. "The Asymmetric Relation Between Initial Margin Requirements and Stock Market Volatility Across Bull and Bear Markets," Review of Financial Studies, Society for Financial Studies, vol. 15(5), pages 1525-1560.
- repec:dgr:kubcen:199658 is not listed on IDEAS
- BAUWENS, Luc & ROMBOUTS, Jeroen, 2003.
"Bayesian clustering of many GARCH models,"
CORE Discussion Papers
2003087, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
- C. S. Wong & W. K. Li, 2000. "On a mixture autoregressive model," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 62(1), pages 95-115.
- Tim Bollerslev, 1986.
"Generalized autoregressive conditional heteroskedasticity,"
EERI Research Paper Series
EERI RP 1986/01, Economics and Econometrics Research Institute (EERI), Brussels.
- Bollerslev, Tim, 1986. "Generalized autoregressive conditional heteroskedasticity," Journal of Econometrics, Elsevier, vol. 31(3), pages 307-327, April.
- Kim, Dongcheol & Kon, Stanley J, 1994. "Alternative Models for the Conditional Heteroscedasticity of Stock Returns," The Journal of Business, University of Chicago Press, vol. 67(4), pages 563-98, October.
- Keith Kuester & Stefan Mittnik & Marc S. Paolella, 2006. "Value-at-Risk Prediction: A Comparison of Alternative Strategies," Journal of Financial Econometrics, Society for Financial Econometrics, vol. 4(1), pages 53-89.
- Markus Haas & Stefan Mittnik & Marc Paolella, 2006.
"Modelling and predicting market risk with Laplace-Gaussian mixture distributions,"
Applied Financial Economics,
Taylor & Francis Journals, vol. 16(15), pages 1145-1162.
- Haas, Markus & Mittnik, Stefan & Paolella, Marc S., 2005. "Modeling and predicting market risk with Laplace-Gaussian mixture distributions," CFS Working Paper Series 2005/11, Center for Financial Studies (CFS).
- Christoffersen, Peter F, 1998. "Evaluating Interval Forecasts," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 39(4), pages 841-62, November.
- Geweke, John & Keane, Michael, 2007. "Smoothly mixing regressions," Journal of Econometrics, Elsevier, vol. 138(1), pages 252-290, May.
When requesting a correction, please mention this item's handle: RePEc:iea:carech:0715. 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: (Patricia Power)
If references are entirely missing, you can add them using this form.