Arbeitspapier

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.

Language: Englisch

Bibliographic citation: Series: IES Working Paper ; No. 10/2008

Classification: Wirtschaft
Single Equation Models; Single Variables: Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
International Financial Markets

Subject: volatility
stochastic volatility models
Kalman filter
volatility proxy
Volatilität
Stochastischer Prozess
Schätztheorie
Theorie

Event: Geistige Schöpfung

(who): Kuchynka, Alexandr

Event: Veröffentlichung

(who): Charles University in Prague, Institute of Economic Studies (IES)

(where): Prague

(when): 2008

Handle: http://hdl.handle.net/10419/83297

Last update: 10.03.2025, 11:43 AM CET

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Arbeitspapier

Associated

Kuchynka, Alexandr
Charles University in Prague, Institute of Economic Studies (IES)

Time of origin

2008

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Volatility extraction using the Kalman filter

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Other Objects (12)

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