Higher-order dependence in the general Power ARCH process and a special case
Author
Abstract
Suggested Citation
Note: The forthcoming version of the paper is C. He, H. Malmsten and T. Teräsvirta: Higher-order dependence in the general Power ARCH process and the role of the power parameter
Download full text from publisher
References listed on IDEAS
- Nelson, Daniel B, 1991. "Conditional Heteroskedasticity in Asset Returns: A New Approach," Econometrica, Econometric Society, vol. 59(2), pages 347-370, March.
- Ding, Zhuanxin & Granger, Clive W. J. & Engle, Robert F., 1993. "A long memory property of stock market returns and a new model," Journal of Empirical Finance, Elsevier, vol. 1(1), pages 83-106, June.
- 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.
- Tim Bollerslev, 1988. "On The Correlation Structure For The Generalized Autoregressive Conditional Heteroskedastic Process," Journal of Time Series Analysis, Wiley Blackwell, vol. 9(2), pages 121-131, March.
- Breidt, F. Jay & Crato, Nuno & de Lima, Pedro, 1998. "The detection and estimation of long memory in stochastic volatility," Journal of Econometrics, Elsevier, vol. 83(1-2), pages 325-348.
- He, Changli & Terasvirta, Timo, 1999.
"Properties of moments of a family of GARCH processes,"
Journal of Econometrics, Elsevier, vol. 92(1), pages 173-192, September.
- He, Changli & Teräsvirta, Timo, 1997. "Properties of Moments of a Family of GARCH Processes," SSE/EFI Working Paper Series in Economics and Finance 198, Stockholm School of Economics.
- 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.
Citations
Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
Cited by:
- Peter S. Sephton, 2009. "Fractional integration in agricultural futures price volatilities revisited," Agricultural Economics, International Association of Agricultural Economists, vol. 40(1), pages 103-111, January.
- Giot, Pierre & Laurent, Sebastien, 2004.
"Modelling daily Value-at-Risk using realized volatility and ARCH type models,"
Journal of Empirical Finance, Elsevier, vol. 11(3), pages 379-398, June.
- Giot, P. & Laurent, S.F.J.A., 2001. "Modelling daily value-at-risk using realized volatility and arch type models," Research Memorandum 026, Maastricht University, Maastricht Research School of Economics of Technology and Organization (METEOR).
- GIOT, Pierre & LAURENT, Sébastien, 2004. "Modelling daily Value-at-Risk using realized volatility and ARCH type models," LIDAM Reprints CORE 1708, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
- Pierre Giot & Sébastien Laurent, 2002. "Modelling Daily Value-at-Risk Using Realized Volatility and ARCH Type Models," Computing in Economics and Finance 2002 52, Society for Computational Economics.
- Pierre Giot & Sébastien Laurent, 2003.
"Value-at-risk for long and short trading positions,"
Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 18(6), pages 641-663.
- GIOT, Pierre & LAURENT, Sébastien, 2001. "Value-at-risk for long and short trading positions," LIDAM Discussion Papers CORE 2001022, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
- GIOT, Pierre & LAURENT, Sébastien, 2003. "Value-at-Risk for long and short trading positions," LIDAM Reprints CORE 1707, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
- Pierre Giot and S»bastien Laurent, 2001. "Value-At-Risk For Long And Short Trading Positions," Computing in Economics and Finance 2001 94, Society for Computational Economics.
- Diongue, Abdou Kâ & Guégan, Dominique, 2007.
"The stationary seasonal hyperbolic asymmetric power ARCH model,"
Statistics & Probability Letters, Elsevier, vol. 77(11), pages 1158-1164, June.
- Abdou Kâ Diongue & Dominique Guegan, 2007. "The Stationary Seasonal Hyperbolic Asymmetric Power ARCH model," Université Paris1 Panthéon-Sorbonne (Post-Print and Working Papers) halshs-00179275, HAL.
- Abdou Kâ Diongue & Dominique Guegan, 2007. "The Stationary Seasonal Hyperbolic Asymmetric Power ARCH model," Post-Print halshs-00179275, HAL.
- van Mierlo, J.G.A., 2001. "Over de verhouding tussen overheid, marktwerking en privatisering. Een economische meta-analyse," Research Memorandum 014, Maastricht University, Maastricht Research School of Economics of Technology and Organization (METEOR).
- Tak Siu & John Lau & Hailiang Yang, 2007. "On Valuing Participating Life Insurance Contracts with Conditional Heteroscedasticity," Asia-Pacific Financial Markets, Springer;Japanese Association of Financial Economics and Engineering, vol. 14(3), pages 255-275, September.
- Diamandis, Panayiotis F. & Drakos, Anastassios A. & Kouretas, Georgios P. & Zarangas, Leonidas, 2011. "Value-at-risk for long and short trading positions: Evidence from developed and emerging equity markets," International Review of Financial Analysis, Elsevier, vol. 20(3), pages 165-176, June.
Most related items
These are the items that most often cite the same works as this one and are cited by the same works as this one.- Carnero, María Ángeles, 2001. "Outliers and conditional autoregressive heteroscedasticity in time series," DES - Working Papers. Statistics and Econometrics. WS ws010704, Universidad Carlos III de Madrid. Departamento de EstadÃstica.
- Franses,Philip Hans & Dijk,Dick van, 2000.
"Non-Linear Time Series Models in Empirical Finance,"
Cambridge Books,
Cambridge University Press, number 9780521779654.
- Franses,Philip Hans & Dijk,Dick van, 2000. "Non-Linear Time Series Models in Empirical Finance," Cambridge Books, Cambridge University Press, number 9780521770415, September.
- Stelios Arvanitis & Antonis Demos, 2004. "Time Dependence and Moments of a Family of Time‐Varying Parameter Garch in Mean Models," Journal of Time Series Analysis, Wiley Blackwell, vol. 25(1), pages 1-25, January.
- Diongue, Abdou Kâ & Guégan, Dominique, 2007.
"The stationary seasonal hyperbolic asymmetric power ARCH model,"
Statistics & Probability Letters, Elsevier, vol. 77(11), pages 1158-1164, June.
- Abdou Kâ Diongue & Dominique Guegan, 2007. "The Stationary Seasonal Hyperbolic Asymmetric Power ARCH model," Post-Print halshs-00179275, HAL.
- Abdou Kâ Diongue & Dominique Guegan, 2007. "The Stationary Seasonal Hyperbolic Asymmetric Power ARCH model," Université Paris1 Panthéon-Sorbonne (Post-Print and Working Papers) halshs-00179275, HAL.
- Harvey,Andrew C., 2013.
"Dynamic Models for Volatility and Heavy Tails,"
Cambridge Books,
Cambridge University Press, number 9781107034723, September.
- Harvey,Andrew C., 2013. "Dynamic Models for Volatility and Heavy Tails," Cambridge Books, Cambridge University Press, number 9781107630024, September.
- Mawuli Segnon & Stelios Bekiros & Bernd Wilfling, 2018.
"Forecasting Inflation Uncertainty in the G7 Countries,"
Econometrics, MDPI, vol. 6(2), pages 1-25, April.
- Mawuli Segnon & Stelios Bekiros & Bernd Wilfling, 2018. "Forecasting Inflation Uncertainty in the G7 Countries," CQE Working Papers 7118, Center for Quantitative Economics (CQE), University of Muenster.
- Dominique Guegan & Bertrand K. Hassani, 2019. "Risk Measurement," Université Paris1 Panthéon-Sorbonne (Post-Print and Working Papers) halshs-02119256, HAL.
- Tarek Bouazizi & Zouhaier Hadhek & Fatma Mrad & Mosbah Lafi, 2021. "Changes in Demand for Crude Oil and its Correlation with Crude Oil and Stock Market Returns Volatilities: Evidence from Three Asian Oil Importing Countries," International Journal of Energy Economics and Policy, Econjournals, vol. 11(3), pages 27-43.
- repec:ags:ijag24:346848 is not listed on IDEAS
- Giuseppe Storti & Cosimo Vitale, 2003. "BL-GARCH models and asymmetries in volatility," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 12(1), pages 19-39, February.
- Tarek Bouazizi & Mongi Lassoued & Zouhaier Hadhek, 2021. "Oil Price Volatility Models during Coronavirus Crisis: Testing with Appropriate Models Using Further Univariate GARCH and Monte Carlo Simulation Models," International Journal of Energy Economics and Policy, Econjournals, vol. 11(1), pages 281-292.
- Scharth, Marcel & Medeiros, Marcelo C., 2009.
"Asymmetric effects and long memory in the volatility of Dow Jones stocks,"
International Journal of Forecasting, Elsevier, vol. 25(2), pages 304-327.
- Marcel Scharth & Marcelo Cunha Medeiros, 2006. "Asymmetric effects and long memory in the volatility of Dow Jones stocks," Textos para discussão 532, Department of Economics PUC-Rio (Brazil).
- Yuanhua Feng & Jan Beran & Sebastian Letmathe & Sucharita Ghosh, 2020. "Fractionally integrated Log-GARCH with application to value at risk and expected shortfall," Working Papers CIE 137, Paderborn University, CIE Center for International Economics.
- Amélie Charles & Olivier Darné, 2019.
"The accuracy of asymmetric GARCH model estimation,"
International Economics, CEPII research center, issue 157, pages 179-202.
- Charles, Amélie & Darné, Olivier, 2019. "The accuracy of asymmetric GARCH model estimation," International Economics, Elsevier, vol. 157(C), pages 179-202.
- Bollerslev, Tim & Engle, Robert F. & Nelson, Daniel B., 1986. "Arch models," Handbook of Econometrics, in: R. F. Engle & D. McFadden (ed.), Handbook of Econometrics, edition 1, volume 4, chapter 49, pages 2959-3038, Elsevier.
- Torben G. Andersen & Tim Bollerslev & Peter F. Christoffersen & Francis X. Diebold, 2005.
"Volatility Forecasting,"
PIER Working Paper Archive
05-011, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania.
- Andersen, Torben G. & Bollerslev, Tim & Christoffersen, Peter F. & Diebold, Francis X., 2005. "Volatility forecasting," CFS Working Paper Series 2005/08, Center for Financial Studies (CFS).
- Torben G. Andersen & Tim Bollerslev & Peter F. Christoffersen & Francis X. Diebold, 2005. "Volatility Forecasting," NBER Working Papers 11188, National Bureau of Economic Research, Inc.
- Andersen, Torben G. & Bollerslev, Tim & Christoffersen, Peter F. & Diebold, Francis X., 2006. "Volatility and Correlation Forecasting," Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.), Handbook of Economic Forecasting, edition 1, volume 1, chapter 15, pages 777-878, Elsevier.
- Amélie Charles & Olivier Darné, 2019. "The accuracy of asymmetric GARCH model estimation," Post-Print hal-01943883, HAL.
- repec:hal:wpaper:hal-01943883 is not listed on IDEAS
- Pardo, Angel & Motengwe, Chris, 2016. "A Study of Seasonality on the Safex Wheat Market," Agrekon, Agricultural Economics Association of South Africa (AEASA), vol. 54(4), March.
- Milton Abdul Thorlie & Lixin Song & Muhammad Amin & Xiaoguang Wang, 2015. "Modeling and forecasting of stock index volatility with APARCH models under ordered restriction," Statistica Neerlandica, Netherlands Society for Statistics and Operations Research, vol. 69(3), pages 329-356, August.
- Christensen, Bent Jesper & Nielsen, Morten Ørregaard & Zhu, Jie, 2010.
"Long memory in stock market volatility and the volatility-in-mean effect: The FIEGARCH-M Model,"
Journal of Empirical Finance, Elsevier, vol. 17(3), pages 460-470, June.
- Bent Jesper Christensen & Morten Ørregaard Nielsen & Jie Zhu, 2007. "Long Memory in Stock Market Volatility and the Volatility-in-Mean Effect: The FIEGARCH-M Model," CREATES Research Papers 2007-10, Department of Economics and Business Economics, Aarhus University.
- Bent Jesper Christensen & Jie Zhu & Morten Ø. Nielsen, 2009. "Long Memory In Stock Market Volatility And The Volatility-in-mean Effect: The Fiegarch-m Model," Working Paper 1207, Economics Department, Queen's University.
More about this item
Keywords
Box-Cox transformation; conditional heteroskedasticity; exponential GARCH; logarithmic GARCH; higher-order dependence;All these keywords.
JEL classification:
- C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
NEP fields
This paper has been announced in the following NEP Reports:- NEP-ETS-1999-05-10 (Econometric Time Series)
Statistics
Access and download statisticsCorrections
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:hhs:hastef:0315. See general information about how to correct material in RePEc.
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 CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .
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.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Helena Lundin (email available below). General contact details of provider: https://edirc.repec.org/data/erhhsse.html .
Please note that corrections may take a couple of weeks to filter through the various RePEc services.