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Explaining Systemic Risk in Money Market Funds

机译:解释货币市场基金的系统性风险

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For the first time, this study evaluates the contributions to systemic risk in the context of U.S. institutional prime money market funds (MMFs) from different sources using partial least squares structural equation modeling (PLS-SEM). The primary motivation behind this study is to trace systemic risk to its underlying sources and measure which types of relationships provide significant explanation using PLS-SEM. I illustrate the application of PLS-SEM and interpretation of results in a step-by-step manner to empower those new to PLS-SEM, and undertake robustness testing. Findings indicate that through crisis years, macroprudential indicators contribute to potential systemic risk more than prudential indicators. This suggests that macroprudential indicators that can be traced to individual MMFs market positions are more important in understanding systemic risk during crises, and further underlines the interconnectedness of markets. PLS-SEM can be used to test the explanatory power of new indicators as they emerge in an exploratory environment.
机译:这项研究首次使用偏最小二乘结构方程模型(PLS-SEM)评估了来自不同来源的美国机构主要货币市场基金(MMF)对系统风险的贡献。这项研究背后的主要动机是使用PLS-SEM追踪系统性风险至其潜在来源,并衡量哪些类型的关系提供了重要的解释。我以逐步的方式说明了PLS-SEM的应用和结果的解释,以增强PLS-SEM的新功能,并进行耐用性测试。研究结果表明,在危机年代,宏观审慎指标对潜在系统风险的贡献要大于审慎指标。这表明可以追溯到各个MMF市场地位的宏观审慎指标在理解危机期间的系统性风险方面更为重要,并进一步突显了市场的相互联系。 PLS-SEM可用于测试在探索环境中出现的新指标的解释能力。

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