We define a nonlinear autoregressive time series model based on the generalized hyperbolic distribution in an attempt to model time series with non‐Gaussian features such as skewness and heavy tails. We show that the resulting process has a simple condition for stationarity and it is also ergodic. An empirical example with a forecasting experiment is presented to illustrate the features of the proposed model.

中文翻译：

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基于广义双曲分布的自回归模型

我们基于广义双曲线分布定义了非线性自回归时间序列模型，以对具有非高斯特征（例如偏度和粗尾）的时间序列建模。我们表明，生成的过程具有平稳的简单条件，并且也是遍历遍历的。给出了一个带有预测实验的经验例子，以说明所提出模型的特征。