Please use this identifier to cite or link to this item: http://hdl.handle.net/10419/25285
Authors: 
Härdle, Wolfgang Karl
Hautsch, Nikolaus
Pigorsch, Uta
Year of Publication: 
2008
Series/Report no.: 
SFB 649 discussion paper 2008,045
Abstract: 
Measuring and modeling financial volatility is the key to derivative pricing, asset allocation and risk management.The recent availability of high-frequency data allows for refined methods in this field.In particular, more precise measures for the daily or lower frequency volatility can be obtained by summing over squared high-frequency returns.In turn, this so-called realized volatility can be used for more accurate model evaluation and description of the dynamic and distributional structure of volatility. Moreover, non-parametric measures af systematic risk are attainable, that can straightforwardly be used to model the commonly observed time-variation in the betas. The discussion of these new measures and methods is accompanied by an empirical illustration using high-frequency data of the IBM incorpration and the DJIA index.
Subjects: 
Realized volatility
realized betas
volatility modeling
JEL: 
C13
C14
C22
C52
C53
Document Type: 
Working Paper

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