GARCH models, tail indexes and error distributions: An empirical investigation
Download full text from publisher
As the access to this document is restricted, you may want to look for a different version below or search for a different version of it.
Other versions of this item:
- Roman Horváth & Boril Sopov, 2015. "GARCH Models, Tail Indexes and Error Distributions: An Empirical Investigation," Working Papers IES 2015/09, Charles University Prague, Faculty of Social Sciences, Institute of Economic Studies, revised May 2015.
References listed on IDEAS
- Groenendijk, Patrick A. & Lucas, Andre & de Vries, Casper G., 1995. "A note on the relationship between GARCH and symmetric stable processes," Journal of Empirical Finance, Elsevier, vol. 2(3), pages 253-264, September.
- Nelson, Daniel B, 1991. "Conditional Heteroskedasticity in Asset Returns: A New Approach," Econometrica, Econometric Society, vol. 59(2), pages 347-370, March.
- Karmakar, Madhusudan, 2013. "Estimation of tail-related risk measures in the Indian stock market: An extreme value approach," Review of Financial Economics, Elsevier, vol. 22(3), pages 79-85.
- repec:adr:anecst:y:2000:i:60 is not listed on IDEAS
- McNeil, Alexander J. & Frey, Rudiger, 2000. "Estimation of tail-related risk measures for heteroscedastic financial time series: an extreme value approach," Journal of Empirical Finance, Elsevier, vol. 7(3-4), pages 271-300, November.
- Huisman, Ronald, et al, 2001. "Tail-Index Estimates in Small Samples," Journal of Business & Economic Statistics, American Statistical Association, vol. 19(2), pages 208-216, April.
- repec:adr:anecst:y:2000:i:60:p:10 is not listed on IDEAS
- Jon Danielsson & Casper G. De Vries, 2000. "Value-at-Risk and Extreme Returns," Annals of Economics and Statistics, GENES, issue 60, pages 239-270.
- 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.
- Bollerslev, Tim, 1986.
"Generalized autoregressive conditional heteroskedasticity,"
Journal of Econometrics,
Elsevier, vol. 31(3), pages 307-327, April.
- Tim Bollerslev, 1986. "Generalized autoregressive conditional heteroskedasticity," EERI Research Paper Series EERI RP 1986/01, Economics and Econometrics Research Institute (EERI), Brussels.
- Longin, Francois M., 2000. "From value at risk to stress testing: The extreme value approach," Journal of Banking & Finance, Elsevier, vol. 24(7), pages 1097-1130, July.
- Wagner, Niklas & Marsh, Terry A., 2005. "Measuring tail thickness under GARCH and an application to extreme exchange rate changes," Journal of Empirical Finance, Elsevier, vol. 12(1), pages 165-185, January.
- Huisman, R. & Koedijik, K.G. & Pownall, R.A.J., 1998. "VaR-x: Fat Tails in Financial Risk Management," Papers 98-54, Southern California - School of Business Administration.
- Robert Engle, 2001. "GARCH 101: The Use of ARCH/GARCH Models in Applied Econometrics," Journal of Economic Perspectives, American Economic Association, vol. 15(4), pages 157-168, Fall.
- Ibragimov, Marat & Ibragimov, Rustam & Kattuman, Paul, 2013. "Emerging markets and heavy tails," Journal of Banking & Finance, Elsevier, vol. 37(7), pages 2546-2559.
- Sun, Pengfei & Zhou, Chen, 2014. "Diagnosing the distribution of GARCH innovations," Journal of Empirical Finance, Elsevier, vol. 29(C), pages 287-303.
- Engle, Robert F, 1982. "Autoregressive Conditional Heteroscedasticity with Estimates of the Variance of United Kingdom Inflation," Econometrica, Econometric Society, vol. 50(4), pages 987-1007, July.
CitationsCitations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
- repec:taf:applec:v:50:y:2018:i:34-35:p:3647-3653 is not listed on IDEAS
- Georgios Bampinas & Konstantinos Ladopoulos & Theodore Panagiotidis, 2018.
"A note on the estimated GARCH coefficients from the S&P1500 universe,"
Taylor & Francis Journals, vol. 50(34-35), pages 3647-3653, July.
- Georgios Bampinas & Konstantinos Ladopoulos & Theodore Panagiotidis, 2017. "A note on the estimated GARCH coefficients from the S&P1500 universe," Working Paper series 17-09, Rimini Centre for Economic Analysis.
- Georgios Bampinas & Konstantinos Ladopoulos & Theodore Panagiotidis, 2017. "A note on the estimated GARCH coefficients from the S&P1500 universe," Discussion Paper Series 2017_04, Department of Economics, University of Macedonia, revised May 2017.
- repec:eee:ecofin:v:42:y:2017:i:c:p:346-358 is not listed on IDEAS
- Guo, Xu & McAleer, Michael & Wong, Wing-Keung & Zhu, Lixing, 2017.
"A Bayesian approach to excess volatility, short-term underreaction and long-term overreaction during financial crises,"
The North American Journal of Economics and Finance,
Elsevier, vol. 42(C), pages 346-358.
- Guo, X. & McAleer, M.J. & Wong, W.-K. & Zhu, L., 2016. "A Bayesian Approach to Excess Volatility, Short-term Underreaction and Long-term Overreaction during Financial Crises," Econometric Institute Research Papers EI2016-01, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
- Xu Guo & Michael McAleer & Wing-Keung Wong & Lixing Zhu, 2016. "A Bayesian Approach to Excess Volatility, Short-term Underreaction and Long-term Overreaction During Financial Crises," Tinbergen Institute Discussion Papers 16-003/III, Tinbergen Institute.
More about this item
KeywordsGARCH; Extreme events; S&P 500 study; Tail index;
- C15 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Statistical Simulation Methods: General
- C58 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Financial Econometrics
- G17 - Financial Economics - - General Financial Markets - - - Financial Forecasting and Simulation
StatisticsAccess and download statistics
All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:ecofin:v:37:y:2016:i:c:p:1-15. 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: (Dana Niculescu). General contact details of provider: http://www.elsevier.com/locate/inca/620163 .
If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.
If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.
Please note that corrections may take a couple of weeks to filter through the various RePEc services.