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英文文献：On IGARCH and convergence of the QMLE for misspecified GARCH models-非指定GARCH模型QMLE的IGARCH和收敛性
英文文献作者：Anders Tolver Jensen,Theis Lange
英文文献摘要：
We address the IGARCH puzzle by which we understand the fact that a GARCH(1,1) model fitted by quasi maximum likelihood estimation to virtually any financial dataset exhibit the property that alpha^hat + beta^hat is close to one. We prove that if data is generated by certain types of continuous time stochastic volatility models, but fitted to a GARCH(1,1) model one gets that alpha^hat + beta^hat tends to one in probability as the sampling frequency is increased. Hence, the paper suggests that the IGARCH effect could be caused by misspecification. The result establishes that the stochastic sequence of QMLEs do indeed behave as the deterministic parameters considered in the literature on filtering based on misspecified ARCH models, see e.g. Nelson (1992). An included study of simulations and empirical high frequency data is found to be in very good accordance with the mathematical results.
我们解决了IGARCH难题，通过该难题，我们了解到一个由拟极大似然估计拟合到几乎任何金融数据集的GARCH(1,1)模型显示了alpha^hat + beta^hat接近于1的属性。我们证明了如果数据是由某些类型的连续时间随机波动模型产生的，但拟合到GARCH(1,1)模型可以得到随着采样频率的增加，alpha^hat + beta^hat在概率上趋向于1。因此，本文认为IGARCH效应可能是由错误描述引起的。结果表明QMLEs的随机序列确实表现为文献中基于错误指定ARCH模型的滤波所考虑的确定性参数，例如Nelson(1992)。包括模拟和经验高频数据的研究发现与数学结果非常一致。
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