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http://hdl.handle.net/10419/23552
  
Title:Modelling Different Volatility Components PDF Logo
Authors:Feng, Yuanhua
Issue Date:2002
Series/Report no.:Discussion paper series / Universität Konstanz, Center of Finance and Econometrics (CoFE) 02/18
Abstract:This paper considers simultaneous modelling of seasonality, slowly changing un- conditional variance and conditional heteroskedasticity in high-frequency fiancial returns. A new approach, called a seasonal SEMIGARCH model, is proposed to perform this by introducing multiplicative seasonal and trend components into the GARCH model. A data-driven semiparametric algorithm is developed for estimat- ing the model. Asymptotic properties of the proposed estimators are investigated briefly. An approximate significance test of seasonality and the use of Monte Carlo confidence bounds for the trend are proposed. Practical performance of the pro- posal is investigated in detail using some German stock price returns. The approach proposed here provides a useful semiparametric extension of the GARCH model.
Subjects:High-frequency financial data
nonparametric regression
seasonality in volatility
semiparametric GARCH model
trend in volatility
Persistent Identifier of the first edition:urn:nbn:de:bsz:352-opus-9481
Document Type:Working Paper
Appears in Collections:CoFE-Diskussionspapiere, Universität Konstanz

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