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中文摘要：
两步优化估计方法IFM是Copula—GARCH模型的重要参数估计方法，但是当研究的样本容量较小时，IFM估计方法会产生较大的估计误差。为了更为准确地估计汇率市场波动，我们运用多步优化估计方法MBP来估计汇率市场中的Copula—MGARCH模型，检验结果表明MBP方法比精确极大似然估计方法更简单、比IFM方法更有效，所获得的汇率波动估计精度更高。
英文摘要：
A two- step optimization method called inference functions for margins （IFM） is broadly adopted to estimate Copula - GARCH models. However, IFM is subject to small - sample bias. This paper proposes to estimate Copula - GARCH models in exchange rate markets by applying Maximization by Parts （MBP）, a multi - step optimization algorithm. This method decomposes the complicated log likelihood into two parts. In the decomposition, the first part is an easy likelihood consisting of only marginal likelihood. The second part includes depend- ence parameters from a multivariate likelihood and is used to update the estimates from the first part. The results indicate that MBP can provide more efficient estimation than IFM.
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