Volatility extraction using the Kalman filter
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.
|Date of creation:||Jun 2008|
|Date of revision:||Jun 2008|
|Contact details of provider:|| Postal: Opletalova 26, CZ-110 00 Prague|
Phone: +420 2 222112330
Fax: +420 2 22112304
Web page: http://ies.fsv.cuni.cz/
More information through EDIRC
When requesting a correction, please mention this item's handle: RePEc:fau:wpaper:wp2008_10. See general information about how to correct material in RePEc.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Lenka Herrmannova)
If references are entirely missing, you can add them using this form.