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英文文献：The limiting properties of the QMLE in a general class of asymmetric volatility models-一类非对称波动率模型中QMLE的极限性质
英文文献作者：Christian M. Dahl,Emma M. Iglesias
英文文献摘要：
In this paper we analyze the limiting properties of the estimated parameters in a general class of asymmetric volatility models which are closely related to the traditional exponential GARCH model. The new representation has three main advantages over the traditional EGARCH: (1) It allows a much more flexible representation of the conditional variance function. (2) It is possible to provide a complete characterization of the asymptotic distribution of the QML estimator based on the new class of nonlinear volatility models, something which has proven very difficult even for the traditional EGARCH. (3) It can produce asymmetric news impact curves where, contrary to the traditional EGARCH, the resulting variances do not excessively exceed the ones associated with the standard GARCH model, irrespectively of the sign of an impact of moderate size. Furthermore, the new class of models considered can create a wide array of news impact curves which provide the researcher with a richer choice set relative to the traditional. We also show in a Monte Carlo experiment the good finite sample performance of our asymptotic theoretical results and we compare them with those obtained from a parametric and the residual based bootstrap. Finally, we provide an empirical illustration.
本文分析了一类与传统指数GARCH模型密切相关的非对称波动率模型的估计参数的极限性质。与传统的EGARCH相比，新的表示法有三个主要优点:(1)它允许条件方差函数的更灵活的表示法。(2)有可能提供基于新一类非线性波动率模型的QML估计量的渐近分布的一个完整的表征，这已经被证明是非常困难的，即使是传统的EGARCH。(3)可以产生非对称的新闻影响曲线，与传统EGARCH相反，其结果的方差并不过分超过标准GARCH模型的方差，不考虑中等规模的影响的符号。此外，所考虑的新一类模型可以创建广泛的新闻影响曲线，为研究者提供了比传统的更丰富的选择集。在蒙特卡洛实验中，我们也展示了我们的渐近理论结果的良好的有限样本性能，并与那些从参数和基于残差的bootstrap得到的结果进行了比较。最后，我们提供了一个实证的例证。
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