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- W2328382783 abstract "We consider a class of semiparametric GARCH models with additive autoregressive components linked together by a dynamic coefficient. We propose estimators for the additive components and the dynamic coefficient based on spline smoothing. The estimation procedure involves only a small number of least squares operations, thus it is computationally efficient. Under regularity conditions, the proposed estimator of the parameter is root-n consistent and asymptotically nor- mal. A simultaneous confidence band for the nonparametric component is proposed by an efficient one-step spline backfitting. The performance of our method is evalu- ated by various simulated processes and a financial return series. For the empirical financial return series, we find further statistical evidence of the asymmetric news impact function." @default.
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- W2328382783 date "2012-01-01" @default.
- W2328382783 modified "2023-10-16" @default.
- W2328382783 title "Efficient semiparametric garch modeling of financial volatility" @default.
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- W2328382783 doi "https://doi.org/10.5705/ss.2009.285" @default.
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