Random coefficient volatility models
AbstractIn financial modeling, the moments of the observed process, the kurtosis and the moments of the conditional volatility play important roles. They are very important in model identification and in forecasting the volatility (see Thavaneswaran et al. [(2005b). Forecasting volatility. Statist. Probab. Lett. 75, 1-10.]). This paper introduces random coefficient GARCH models including the class random coefficient GARCH (RC-GARCH) models and derive their higher order moments and kurtosis.
Download InfoIf you experience problems downloading a file, check if you have the proper application to view it first. In case of further problems read the IDEAS help page. Note that these files are not on the IDEAS site. Please be patient as the files may be large.
As the access to this document is restricted, you may want to look for a different version under "Related research" (further below) or search for a different version of it.
Bibliographic InfoArticle provided by Elsevier in its journal Statistics & Probability Letters.
Volume (Year): 78 (2008)
Issue (Month): 6 (April)
Contact details of provider:
Web page: http://www.elsevier.com/wps/find/journaldescription.cws_home/622892/description#description
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.:
- Bovas Abraham & A. Thavaneswaran, 1991. "A nonlinear time series model and estimation of missing observations," Annals of the Institute of Statistical Mathematics, Springer, vol. 43(3), pages 493-504, September.
- Thavaneswaran, A. & Appadoo, S.S. & Peiris, S., 2005. "Forecasting volatility," Statistics & Probability Letters, Elsevier, vol. 75(1), pages 1-10, November.
- Fornari, F. & Mele, A., 1995.
"Sign- and Volatility -Switching ARCH Models: Theory and Applications to International Stock Markets,"
251, Banca Italia - Servizio di Studi.
- Fornari, Fabio & Mele, Antonio, 1997. "Sign- and Volatility-Switching ARCH Models: Theory and Applications to International Stock Markets," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 12(1), pages 49-65, Jan.-Feb..
- 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.
- 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.
- 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.
- He, Changli & Teräsvirta, Timo, 1997.
"Properties of Moments of a Family of GARCH Processes,"
Working Paper Series in Economics and Finance
198, Stockholm School of Economics.
- 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.
- Sabiruzzaman, Md. & Monimul Huq, Md. & Beg, Rabiul Alam & Anwar, Sajid, 2010. "Modeling and forecasting trading volume index: GARCH versus TGARCH approach," The Quarterly Review of Economics and Finance, Elsevier, vol. 50(2), pages 141-145, May.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Zhang, Lei).
If references are entirely missing, you can add them using this form.