Volatility extraction using the Kalman filter - Alexandr Kuchynka (Charles University in Prague, Institute of Economic Studies (IES), 2008)
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.
Keywords: C22; G15; 330; volatility; stochastic volatility models; Kalman filter; volatility proxy; Volatilität; Stochastischer Prozess; Schätztheorie; Theorie