TESTING THE STRUCTURE OF CONDITIONAL CORRELATIONS IN MULTIVARIATE GARCH MODELS: A GENERALIZED CROSS-SPECTRUM APPROACH

• 成果类型: Article
• 署名作者: McCloud, Nadine; Hong, Yongmiao
• 署名单位: Cornell University; University West Indies Mona Jamaica; Xiamen University
• 刊物名称: INTERNATIONAL ECONOMIC REVIEW
• ISSN/ISSBN: 0020-6598
• DOI: 10.1111/j.1468-2354.2011.00657.x
• 发表日期: 2011
• 页码: 991-1037
• 关键词: Asymptotic Theory; time-series; constant; volatility; heteroskedasticity; transmission; Consistency; returns

摘要

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.