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Asymmetry Effects in Chinese Stock Markets Volatility: A Generalized Additive Nonparametric Approach

HOU, Ai Jun LU (2007)
Abstract
The unique characteristics of the Chinese stock markets make it difficult to assume a particular distribution for innovations in returns and the specification form of the volatility process when modeling return volatility with the parametric GARCH family models. This paper therefore applies a generalized additive nonparametric smoothing technique to examine the volatility of the Chinese stock markets. The empirical results indicate that an asymmetric effect of negative news exists in the Chinese stock markets. Furthermore, compared with other parametric and nonparametric models, the generalized additive nonparametric model demonstrates a better performance for return volatility forecasts, particularly for the out-of-sample forecast. The... (More)
The unique characteristics of the Chinese stock markets make it difficult to assume a particular distribution for innovations in returns and the specification form of the volatility process when modeling return volatility with the parametric GARCH family models. This paper therefore applies a generalized additive nonparametric smoothing technique to examine the volatility of the Chinese stock markets. The empirical results indicate that an asymmetric effect of negative news exists in the Chinese stock markets. Furthermore, compared with other parametric and nonparametric models, the generalized additive nonparametric model demonstrates a better performance for return volatility forecasts, particularly for the out-of-sample forecast. The generalized additive nonparametric technique has the potential to be widely applied to other emerging stock markets that have similar characteristics to the Chinese stock markets. (Less)
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author
organization
publishing date
type
Working Paper
publication status
submitted
subject
keywords
Chinese stock market, Asymmetry effect, Nonparametric GARCH model, News
pages
34 pages
language
English
LU publication?
yes
id
eddbc857-428d-4359-b1ac-1d16c0ea579f (old id 1763379)
date added to LUP
2011-01-21 15:03:16
date last changed
2016-04-16 12:08:42
@misc{eddbc857-428d-4359-b1ac-1d16c0ea579f,
  abstract     = {The unique characteristics of the Chinese stock markets make it difficult to assume a particular distribution for innovations in returns and the specification form of the volatility process when modeling return volatility with the parametric GARCH family models. This paper therefore applies a generalized additive nonparametric smoothing technique to examine the volatility of the Chinese stock markets. The empirical results indicate that an asymmetric effect of negative news exists in the Chinese stock markets. Furthermore, compared with other parametric and nonparametric models, the generalized additive nonparametric model demonstrates a better performance for return volatility forecasts, particularly for the out-of-sample forecast. The generalized additive nonparametric technique has the potential to be widely applied to other emerging stock markets that have similar characteristics to the Chinese stock markets.},
  author       = {HOU, Ai Jun},
  keyword      = {Chinese stock market,Asymmetry effect,Nonparametric GARCH model,News},
  language     = {eng},
  pages        = {34},
  title        = {Asymmetry Effects in Chinese Stock Markets Volatility: A Generalized Additive Nonparametric Approach},
  year         = {2007},
}