Testing the Structure of Conditional Correlations in Multivariate GARCH Models: A Generalized Cross‐Spectrum Approach
Testing the Structure of Conditional Correlations in Multivariate GARCH Models: A Generalized Cross‐Spectrum Approach
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测试多元 GARCH 模型中的条件相关结构：广义跨谱方法
DOI：
10.1111/j.1468-2354.2011.00657.x
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发表时间：
2011
期刊：
影响因子：
--
通讯作者：
Yongmiao Hong
中科院分区：
文献类型：
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作者：
N. McCloud;Yongmiao Hong
我们介绍了一类普遍适用的规格测试的常数和动态结构的条件相关的多元Gesthem模型。测试是强大的存在下，随时间变化的高阶条件矩的未知形式，是纯粹的显着性测试。该检验可以识别条件相关中的线性和非线性误设定。我们的方法不需要一个特定的参数估计方法和分布假设的误差过程。检验的渐近分布对参数估计中的不确定性是不变的。我们使用模拟和真实的数据来评估我们的测试的有限样本性能。
We introduce a class of generally applicable specification tests for constant and dynamic structures of conditional correlations in multivariate GARCH models. The tests are robust to the presence of time-varying higher-order conditional moments of unknown form and are pure significance tests. The tests can identify linear and nonlinear misspecifications in conditional correlations. Our approach does not necessitate a particular parameter estimation method and distributional assumption on the error process. The asymptotic distribution of the tests is invariant to the uncertainty in parameter estimation. We assess the finite sample performance of our tests using simulated and real data.