مقاله انگلیسی رایگان در مورد در نظر گرفتن موضوع یا ریسک برای شکست – الزویر ۲۰۱۹

In this study we hypothesise that more frequent extreme negative daily equity returns result in higher tail risk, and this subsequently increases firms’ likelihood of entering financial distress. Specifically, we investigate the role of Value-at-risk and Expected Shortfall in aggravating firms’ likelihood of experiencing financial distress. Our results show that longer horizon (three- and five-year) tail risk measures contributes positively toward firms’ likelihood of experiencing financial distress. Additionally, considering the declining number of bankruptcy filings, and increasing out-of-court negotiations and debt reorganisations, we argue in favour of penalising firms for becoming sufficiently close to bankruptcy that they have questionable going-concern status. Thus, we propose a definition of financial distress contingent upon firms’ earnings, financial expenses, market value and operating cash flow.

Introduction

Financial Distress and Tail Risk are two apparently diverse topics that are gaining increasing attention in the corporate finance literature. The financial crisis of 2007–۰۸ was the alarm bell that augmented global awareness toward tail risk among financial risk managers. Since then, we have witnessed increasing concern among stakeholders toward firms’ risk of bankruptcy or financial distress. Although tail risk has been an active area of investigation in the domain concerned with large financial institutions and financial stability, to the best of our knowledge this study is the first academic attempt to address the relationship between firms’ extreme negative daily equity returns and their likelihood of experiencing financial distress. We hypothesise that more frequent extreme negative daily equity returns result in higher tail risk, and this subsequently increases firms’ likelihood of entering financial distress. The vast majority of academic literature on bankruptcy prediction gravitates around either the choice of explanatory variables (e.g. Campbell, Hilscher, & Szilagyi, 2008; Jones, 2017), or modelling methodologies (e.g. Gupta, Gregoriou, & Ebrahimi, 2018; Shumway, 2001) targeted toward optimising models’ classification performance. However, a model’s performance is significantly dependent on how the distress or bankruptcy event is defined in the first place.