Parameter estimation for GARCH(1,1) models based on Kalman filter. (English) Zbl 1279.62178
Summary: 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.
MSC:
62M10 | Time series, auto-correlation, regression, etc. in statistics (GARCH) |
62F10 | Point estimation |
93E11 | Filtering in stochastic control theory |