Advances and Applications in Statistics
Volume 25, Issue 2, Pages 115 - 130
(December 2011)
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PARAMETER ESTIMATION FOR GARCH(1, 1) MODELS BASED ON KALMAN FILTER
Jelloul Allal and Mohammed Benmoumen
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Abstract: In this work, we propose a new estimate algorithm for the parameters of a GARCH(1, 1) model. This algorithm turns out to be very reliable in estimating the true parameter values of a given model. It combines quasi-maximum likelihood method, Kalman filter algorithm and the SPSA method (Simultaneous Perturbation Stochastic Approximation). Simulation results demonstrate that the algorithm is viable and promising. |
Keywords and phrases: GARCH models, quasi-maximum likelihood, Kalman filter, simultaneous perturbation stochastic approximation. |
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