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Garch model indentification using neural network

机译:基于神经网络的Garch模型识别

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GARCH models are being largely used to estimate the volatility offinancial assets, and GARCH(1,1) is the one most used. However, identificationof GARCH models is not fully explored. Some specialist systems technology havebeen used in some applications of time series models such as time seriesclassification problems, ARMA models identification, as well as SARIMA. The aim of this paper is to develop an intelligent system that can accurately identifythe specification of GARCH models providing the right choice of the model to beused, thus avoiding the indiscriminate usage of GARCH(1,1) model.
机译:GARCH模型主要用于估计金融资产的波动性,而GARCH(1,1)是最常用的模型。但是,尚未完全探索GARCH模型的识别。时间序列模型的某些应用中已经使用了一些专业的系统技术,例如时间序列分类问题,ARMA模型识别以及SARIMA。本文的目的是开发一种智能系统,该系统可以准确地识别GARCH模型的规格,从而为要使用的模型提供正确的选择,从而避免随意使用GARCH(1,1)模型。

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