股票-债券长期相关性的宏观金融决定因素:DCC-MIDAS规范

Hossein Asgharian, C. Christiansen, A. Hou
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引用次数: 99

摘要

我们使用一个模型来研究长期股票-债券相关性,该模型结合了动态条件相关模型和混合数据抽样方法,并允许长期相关性受到宏观金融因素(历史和预测)的影响。我们使用与通货膨胀和利率、流动性不足、经济状况和市场不确定性相关的宏观金融因素。宏观金融因素,尤其是它们的预测,善于预测长期的股票-债券相关性。当经济疲软时,长期相关性往往很小,甚至为负,这支持了“逃向优质资产”的现象。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Macro-Finance Determinants of the Long-Run Stock-Bond Correlation: The DCC-MIDAS Specification
We investigate long-run stock–bond correlation using a model that combines the dynamic conditional correlation model with the mixed-data sampling approach and allows long-run correlation to be affected by macro-finance factors (historical and forecasts). We use macro-finance factors related to inflation and interest rates, illiquidity, state of the economy, and market uncertainty. Macro-finance factors, particularly their forecasts, are good at forecasting long-run stock–bond correlation. Supporting the flight-to-quality phenomenon, long-run correlation tends to be small and negative when the economy is weak.
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