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Modeling and forecasting volatility of Shanghai Stock Exchange with GARCH family models

This paper discusses the performance of modeling and forecasting volatility ofdaily stock returns of A-shares in Shanghai Stock Exchange. The volatility is modeledby GARCH family models which are GARCH, EGARCH and GJR-GARCHmodels with three distributions, namely Gaussian distribution, student-t distributionand generalized error distribution (GED). In order to determine the performanceof forecasting volatility, we compare the models by using the Root MeanSquared Error (RMSE). The results show that the EGARCH models work so wellin most of daily stock returns and the symmetric GARCH models are better thanasymmetric GARCH models in this paper.

Identiferoai:union.ndltd.org:UPSALLA1/oai:DiVA.org:uu-155066
Date January 2011
CreatorsHan, Yang
PublisherUppsala universitet, Statistiska institutionen
Source SetsDiVA Archive at Upsalla University
LanguageEnglish
Detected LanguageEnglish
TypeStudent thesis, info:eu-repo/semantics/bachelorThesis, text
Formatapplication/pdf
Rightsinfo:eu-repo/semantics/openAccess

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