在大流行之前预测与COVID-19相关的公司破产

Q4 Economics, Econometrics and Finance
Annhenrie Campbell, Gökçe Tan Kim B. Soydemir
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引用次数: 0

摘要

在先前的研究中,研究表明,濒临破产的企业比基于SIC(标准行业分类)代码的配对匹配企业表现出更少的混乱。混沌可以用来比较通过计算李雅普诺夫指数量化的系统。在本研究中,指数是使用股票市场日收益的时间序列来计算的。鉴于不健康系统比健康系统表现出更少的混乱,破产在本研究中被认为是不健康系统的一种表达。COVID-19大流行的突然出现给企业带来了压力。本研究成功地使用了基于新NAICS(北美工业分类系统)代码的配对公司计算的Lyapunov指数,以预测流行病出现后不久发生的破产。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Predicting COVID-19 Related Corporate Bankruptcies Prior to the Pandemic
In a previous study, it was shown that firms approaching bankruptcy exhibited less chaos than pair match firms based on their SIC (standard industry classification) code that did not enter bankruptcy. Chaos can be used to compare systems as quantified by calculating the Lyapunov exponent. In this study, the exponent was calculated using time series of daily stock market returns. Given that unhealthy systems display less chaos than healthy systems, bankruptcy is considered in this study as an expression of an unhealthy system. The sudden emergence of the COVID-19 pandemic placed firms under stress. This study successfully uses the Lyapunov exponents calculated for pair match firms based on the newer NAICS (North American Industry Classification System) code prior to the emergence of the pandemic to predict bankruptcies occurring shortly afterwards.
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来源期刊
Universal Journal of Accounting and Finance
Universal Journal of Accounting and Finance Economics, Econometrics and Finance-Finance
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