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首页> 外文期刊>Cogent Economics & Finance >Robust tests for ARCH in the presence of a misspecified conditional mean: A comparison of nonparametric approaches
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Robust tests for ARCH in the presence of a misspecified conditional mean: A comparison of nonparametric approaches

机译：在错过的条件平均值的存在下，拱门的鲁棒测试：非参数方法的比较

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This study compares the size and power of autoregressive conditional heteroskedasticity (ARCH) tests that are robust to the presence of a misspecified conditional mean. The approaches employed are based on two nonparametric regressions for the conditional mean: an ARCH test with a Nadaraya-Watson kernel regression and an ARCH test using a polynomial approximation regression. The two approaches do not require the specification of a conditional mean and can adapt to various nonlinear models, which are unknown a priori. The results reveal that the ARCH tests are robust to the misspecfied conditional mean models. The simulation results show that the ARCH tests based on the polynomial approximation regression approach have better properties of the size and power than those using the Nadaraya-Watson kernel regression approach for various nonlinear models.
机译：本研究比较了自回归条件异源性瘢痕度（拱形）测试的尺寸和功率，这对错过的条件平均值的存在鲁棒。所采用的方法基于条件均值的两个非参数回归：使用多项式近似回归的Nadaraya-Watson内核回归和ARCH测试的ARCH测试。这两种方法不需要条件均值并且可以适应各种非线性模型，这是未知的先验。结果表明，拱门测试对误操作的条件均值均值均匀。仿真结果表明，基于多项式近似回归方法的拱形测试具有比使用各种非线性模型的Nadaraya-Watson核回归方法的大小和功率的更好的特性。

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