Forecasting volatility in the Chinese stock market under model uncertainty

Yong Li (gibbsli@ruc.edu.cn), Wei-Ping Huang and Jie Zhang

Economic Modelling, 2013, vol. 35, issue C, 231-234

Abstract: Volatility forecasting is an important issue in empirical finance. In this paper, the main purpose is to apply the model averaging techniques to reduce volatility model uncertainty and improve volatility forecasting. Six GARCH-type models are considered as candidate models for model averaging. As to the Chinese stock market, the largest emerging market in the world, the empirical study shows that forecast combination using model averaging can be a better approach than the individual forecasts.

Keywords: Chinese stock market; Forecast combination; Forecast accuracy; Model averaging; Volatility forecasting (search for similar items in EconPapers)
JEL-codes: C11 C12 (search for similar items in EconPapers)
Date: 2013
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (13)

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S026499931300271X
Full text for ScienceDirect subscribers only

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:eee:ecmode:v:35:y:2013:i:c:p:231-234

DOI: 10.1016/j.econmod.2013.07.006

Access Statistics for this article

Economic Modelling is currently edited by S. Hall and P. Pauly

More articles in Economic Modelling from Elsevier
Bibliographic data for series maintained by Catherine Liu (repec@elsevier.com).