论文标题
时变性分散整数值garch型号
Time-Varying Dispersion Integer-Valued GARCH Models
论文作者
论文摘要
我们提出了一类全体价值的广义自动回归有条件异质的（INGARCH）过程，通过允许时变均值和分散参数，我们将其称为随时间变化的分散ingarch（TV-Dingarch）模型。更具体地说，我们考虑混合泊松Ingarch模型，并允许分散参数的动态建模（以及均值），类似于普通Garch模型的精神。我们得出条件，以获得一阶和二阶的平稳性以及奇迹性。解决了参数的估计，并且还建立了其相关的渐近特性。提出了一个受限制的引导程序，以测试针对时变化的恒定分散。提出了蒙特卡洛模拟研究，用于检查点估计，标准误差以及受限制的引导方法的性能。我们将电视 - 划线过程从2001年1月到2013年5月，对德国北莱茵 - 韦斯特法里亚的每周报告的麻疹感染数量进行建模，并将其性能与普通的Ingarch方法进行比较。
We propose a general class of INteger-valued Generalized AutoRegressive Conditionally Heteroscedastic (INGARCH) processes by allowing time-varying mean and dispersion parameters, which we call time-varying dispersion INGARCH (tv-DINGARCH) models. More specifically, we consider mixed Poisson INGARCH models and allow for dynamic modeling of the dispersion parameter (as well as the mean), similar to the spirit of the ordinary GARCH models. We derive conditions to obtain first and second-order stationarity, and ergodicity as well. Estimation of the parameters is addressed and their associated asymptotic properties are established as well. A restricted bootstrap procedure is proposed for testing constant dispersion against time-varying dispersion. Monte Carlo simulation studies are presented for checking point estimation, standard errors, and the performance of the restricted bootstrap approach. We apply the tv-DINGARCH process to model the weekly number of reported measles infections in North Rhine-Westphalia, Germany, from January 2001 to May 2013, and compare its performance to the ordinary INGARCH approach.
