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Stability of nonlinear stochastic recursions with application to nonlinear AR-GARCH models

机译:非线性随机递归的稳定性及其在非线性AR-GARCH模型中的应用

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摘要

We characterize the Lyapunov exponent and ergodicity of nonlinear stochastic recursion models, including nonlinearAR-GARCH models, in terms of an easily defined, uniformly ergodic process. Properties of this latter process, known as the collapsed process, also determine the existence of moments for the stochastic recursion when it is stationary. As a result, both the stability of a given model and the existence of its moments may be evaluated with relative ease. The method of proof involves piggybacking a Foster-Lyapunov drift condition on certain characteristic behavior of the collapsed process.
机译:我们用易于定义的均匀遍历过程来表征非线性随机递归模型(包括非线性AR-GARCH模型)的Lyapunov指数和遍历性。后一种过程的特性(称为塌陷过程)也确定了随机递归固定时矩的存在。结果,既可以相对轻松地评估给定模型的稳定性,又可以评估其力矩。证明方法涉及在崩溃过程的某些特征行为上piggy带Foster-Lyapunov漂移条件。

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