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Modeling and forecasting volatility of Shanghai Stock Exchange with GARCH family models
Uppsala University, Disciplinary Domain of Humanities and Social Sciences, Faculty of Social Sciences, Department of Statistics.
2011 (English)Independent thesis Advanced level (degree of Master (Two Years)), 20 credits / 30 HE creditsStudent thesis
Abstract [en]

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.

Place, publisher, year, edition, pages
2011. , 38 p.
Keyword [en]
Volatility GARCH models
Identifiers
URN: urn:nbn:se:uu:diva-155066OAI: oai:DiVA.org:uu-155066DiVA: diva2:423573
Subject / course
Statistics
Educational program
Master Programme in Statistics
Presentation
2011-05-23, B115, Economikum, Uppsala, 13:00 (English)
Uppsok
Social and Behavioural Science, Law
Supervisors
Examiners
Available from: 2011-06-20 Created: 2011-06-15 Last updated: 2011-06-20Bibliographically approved

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Han, Yang
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