测量金融关联性与系统性风险的频率动态
Measuring the frequency dynamics of financial connectedness and systemic risk
AI总结：
本文提出一种新框架，用于测量因异质频率响应而产生的金融变量关联性，通过频谱表示方差分解估计短期、中期和长期金融周期中的关联性，并发现美国金融机构波动性关联性的丰富时频动态。
摘要：
我们提出了一种新的框架，用于测量由于对冲击的异质频率响应而产生的金融变量之间的关联性。为了估计短期、中期和长期金融周期中的关联性，我们引入基于方差分解频谱表示的框架。在实证应用中，我们记录了美国金融机构波动性关联性的丰富时频动态。经济上，高频率产生关联性的时期表明股票市场似乎快速而冷静地处理信息，且系统中一个资产的冲击主要在短期内产生影响。当关联性在较低频率下产生时，这表明冲击是持久的，并且会被更长时间地传递。
英文摘要：
We propose a new framework for measuring connectedness among financial variables that arises due to heterogeneous frequency responses to shocks. To estimate connectedness in short-, medium-, and long-term financial cycles, we introduce a framework based on the spectral representation of variance decompositions. In an empirical application, we document the rich time-frequency dynamics of volatility connectedness in US financial institutions. Economically, periods in which connectedness is created at high frequencies are periods when stock markets seem to process information rapidly and calmly, and a shock to one asset in the system will have an impact mainly in the short term. When the connectedness is created at lower frequencies, it suggests that shocks are persistent and are being transmitted for longer periods.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
