Smooth transition moving average models: Estimation, testing, and computation
提出一类新的非线性移动平均模型（STMA），研究其概率性质，证明最小二乘估计的强相合性和渐近正态性，并给出基于得分的拟合优度检验。通过模拟和汇率数据示例验证方法有效性。
The article introduces a new subclass of nonlinear moving average model, called the smooth transition moving average (STMA) model, and studies its probabilistic properties. It is shown that, under some mild conditions, the least squares estimation (LSE) is strongly consistent and asymptotically normal. A powerful score‐based goodness‐of‐fit test for the STMA model is presented. A different parametrization from the classical one is applied to numerically improve the identification and estimation of this model. Simulation studies are conducted to assess the performance of the LSE and the score‐based test in finite samples. The results are illustrated with an application to the weekly exchange rate of the USA Dollar to the British Pound.