危机时期的投资组合风险管理:动态条件相关性视角

IF 4.6 Q2 MATERIALS SCIENCE, BIOMATERIALS
Hanyu Zhang , Alfonso Dufour
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引用次数: 0

摘要

本文研究了主权债务危机期间欧洲主要政府债券之间的相关性。我们将日内动态条件相关性(DCC)模型应用于 MTS 市场的高频报价数据。我们发现,意大利和西班牙政府债券与其他国家债务的相关性降低,两国债务的相关性随时间大幅波动,从 0.1 到 0.9 不等。欧洲央行的证券市场计划成功地恢复了市场对欧元区完整性的信心,将相关性提高到危机前的水平。此外,我们还研究了计算和预测日内风险价值的四种不同方法,即历史模拟、恒定条件相关性(CCC)模型、双变量 DCC 模型和通过复合似然估计的多变量 DCC 模型。我们证明,双变量 DCC 模型最能预测分布尾部的当日风险价值率。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Managing portfolio risk during crisis times: A dynamic conditional correlation perspective

In this paper, we examine correlations between major European government bonds during the sovereign debt crisis. We apply an intraday Dynamic Conditional Correlation (DCC) model to the high-frequency quote data of the MTS market. We find that the Italian and Spanish government bonds become less correlated with other countries’ debts and the correlation between the two countries’ debts fluctuates heavily over time, ranging from 0.1 to 0.9. The Securities Markets Programme of the ECB is successful in restoring the market confidence for the integrity of the Eurozone, increasing the correlations towards the level before the crisis. In addition, we examine four different methods for computing and forecasting intraday VaR, namely, historical simulation, the Constant Conditional Correlation (CCC) model, the bivariate DCC model, and the multivariate DCC model estimated by composite likelihood. We demonstrate that the bivariate DCC model is most capable of forecasting intraday VaR for the tail of the distribution.

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来源期刊
ACS Applied Bio Materials
ACS Applied Bio Materials Chemistry-Chemistry (all)
CiteScore
9.40
自引率
2.10%
发文量
464
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