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A volatility estimation method based on generalized additive model

By introducing generalized additive model,the restrictions on the parametric form of the conventional GARCH model was broadened. An improved estimation algorithm based on \[Bhlmann P,McNeil A J. An algorithm for nonparametric GARCH modelling. Computational Statistics and Data Analysis,2002,40(4):665-683] has been proposed to estimate the additive GARCH models. The mathematic simulation experiments involving different volatility structures show that the additive GARCH models perform better than the traditional GARCH models employing both in-sample and out-of-sample methods. The additive GARCH models also exceed general nonparametric models. An interential empirical study shows that the additive GARCH model is practically meaningful in studying the volatilities of stock markets which involve complicated characteristics,such as emerging stock markets or stock markets in financial crisis.