Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/83297 
Year of Publication: 
2008
Series/Report no.: 
IES Working Paper No. 10/2008
Publisher: 
Charles University in Prague, Institute of Economic Studies (IES), Prague
Abstract: 
This paper focuses on the extraction of volatility of financial returns. The volatility process is modeled as a superposition of two autoregressive processes which represent the more persistent factor and the quickly mean-reverting factor. As the volatility is not observable, the logarithm of the daily high-low range is employed as its proxy. The estimation of parameters and volatility extraction are performed using a modified version of the Kalman filter which takes into account the finite sample distribution of the proxy.
Subjects: 
volatility
stochastic volatility models
Kalman filter
volatility proxy
JEL: 
C22
G15
Document Type: 
Working Paper

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