Modeling Distress in US High Yield Mutual Funds Before and During the Covid-19 Pandemic

Łukasz Szymczyk, Richard Van Horne, Katarzyna Perez
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引用次数: 1

Abstract

Abstract Research background: In March 2020, when the US financial markets were in the grip of the COVID-19 crisis, the Fed instituted various policies and programs to alleviate stress in financial markets. One such program involved the Fed purchase of securities and ETFs in certain market segments, including high yield bonds. This buying action inspired investors to join the Fed (or front-run the Fed) in the high yield bond market, resulting in the tightening of spreads in that market to historically tight levels. Purpose: In this research we investigate whether investors could have seen any signs of higher liquidity risk in US high yield mutual funds since the beginning of COVID-19 pandemic and avoid it. Theoretically, funds with heightened liquidity risk should have higher historical returns (adjusted for interest rate risk and credit risk) because borne risk requires return as compensation. But because of the unusual market conditions during the COVID-19 pandemic investors could look inside funds (to see what bonds the funds owned) and then avoid funds with holdings known to be less liquid. Research methodology: The study is based on data on US mutual funds from the Morningstar Direct database. The authors made a serial correlation model with an AR(1) process and the lagged effects model vs CAPM model to measure two proxies for liquidity risk for each US high yield mutual fund in our fund universe, in order to identify those funds at particular risk for portfolio illiquidity since the beginning of the COVID-19 pandemic. Results: it is found that the proposed measures may be an effective tool for selecting high yield funds against liquidity risk. Therefore, they should be considered by investors or analysts as a practical tool to identify funds that might be illiquid. Novelty: The study focuses on the liquidity risk in US high yield bond mutual funds before and after the outbreak of the COVID-19 pandemic, which was a crisis situation with implications for liquidity risk. The methods used and results achieved may be a basis for studies of other types of funds and markets outside the USA.
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在Covid-19大流行之前和期间建模美国高收益共同基金的困境
研究背景:2020年3月,当美国金融市场陷入新冠肺炎危机之际,美联储出台了各种缓解金融市场压力的政策和计划。其中一项计划涉及美联储购买某些细分市场的证券和etf,包括高收益债券。这种购买行为促使投资者在高收益债券市场加入美联储(或抢在美联储前面)的行列,导致该市场的利差收窄至历史上的紧缩水平。目的:在本研究中,我们调查了自COVID-19大流行开始以来,投资者是否可以看到美国高收益共同基金出现流动性风险上升的迹象,并避免这种风险。理论上,流动性风险高的基金应该有更高的历史回报(经利率风险和信用风险调整后),因为承担的风险需要回报作为补偿。但由于2019冠状病毒病大流行期间不同寻常的市场状况,投资者可以查看基金内部(看看这些基金持有哪些债券),然后避开那些已知资产流动性较差的基金。研究方法:该研究基于晨星直接数据库中美国共同基金的数据。作者使用AR(1)过程和滞后效应模型与CAPM模型建立了一个序列相关模型,以衡量我们基金领域中每个美国高收益共同基金的流动性风险的两个代理,以便识别自COVID-19大流行开始以来投资组合缺乏流动性的特定风险的基金。结果:本文提出的措施可能是一个有效的工具,以选择高收益的基金,以对抗流动性风险。因此,投资者或分析师应将其视为识别可能缺乏流动性的基金的实用工具。新颖性:研究的重点是新冠肺炎疫情爆发前后美国高收益债券共同基金的流动性风险,这是一种对流动性风险产生影响的危机局面。所使用的方法和取得的结果可能是研究美国以外其他类型的基金和市场的基础。
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