Improving the Forecasting Power of Volatility Models

Ahmed BenSaïda

International Journal of Academic Research in Accounting, Finance and Management Sciences, 2012, vol. 2, issue 3, 51-64

Abstract: Volatility models have been extensively used in risk modeling especially GARCH models under the normal distribution. Although they generate highly significant coefficient estimates, these models are known to have poor forecasting power. It is therefore interesting to develop a different approach of risk modeling to improve forecasting results. By using the generalized t-distribution in modeling the changes in the distribution of stock index returns, the results show a significant improvement in the forecasting power. Moreover, Monte Carlo simulations have confirmed that the index returns are better explained by ARCH-type models.

Keywords: Generalized t; GARCH; forecast; index return (search for similar items in EconPapers)
JEL-codes: C12 C13 C15 C16 C22 G12 G15 (search for similar items in EconPapers)
Date: 2012
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

Downloads: (external link)
http://www.hrmars.com/admin/pics/958.pdf (application/pdf)
http://www.hrmars.com/admin/pics/958.pdf (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:hur:ijaraf:v:2:y:2012:i:3:p:51-64

Access Statistics for this article

More articles in International Journal of Academic Research in Accounting, Finance and Management Sciences from Human Resource Management Academic Research Society, International Journal of Academic Research in Accounting, Finance and Management Sciences
Bibliographic data for series maintained by Hassan Danial Aslam ().