In this paper, we evaluate the QMLKF algorithm, designed in the previous paper [Benmoumen M. Numerical optimization of the likelihood function based on Kalman Filter in the GARCH models. Mathematical Modeling and Computing. 9 (3), 599–606 (2022)] for parameter estimation of GARCH models, by transposing it to real data and then present our machine learning for forecasting the returns of some stock indices.
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