Regulation and Information Costs of Sovereign Distress: Evidence from Corporate Lending Markets
Iftekhar Hasan, Suk-Joong Kim, Panagiotis Politsidis, Eliza Wu
Journal of Corporate Finance,
October
2023
Abstract
We examine the effect of sovereign credit impairments on the pricing of syndicated loans following rating downgrades in the borrowing firms' countries of domicile. We find that the sovereign ceiling policies used by credit rating agencies create a disproportionately adverse impact on the bounded firms' borrowing costs relative to other domestic firms following their sovereign's rating downgrade. Rating-based regulatory frictions partially explain our results. On the supply-side, loans carry a higher spread when granted from low-capital banks, non-bank lenders, and banks with high market power. We further document an operating demand-side channel, contingent on borrowers' size, financial constraints, and global diversification. Our results can be attributed to the relative bargaining power between lenders and borrowers: relationship borrowers and non-bank dependent borrowers with alternative financing sources are much less affected.
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"Let Me Get Back to You" — A Machine Learning Approach to Measuring NonAnswers
Andreas Barth, Sasan Mansouri, Fabian Wöbbeking
Management Science,
No. 10,
2023
Abstract
Using a supervised machine learning framework on a large training set of questions and answers, we identify 1,364 trigrams that signal nonanswers in earnings call questions and answers (Q&A). We show that this glossary has economic relevance by applying it to contemporaneous stock market reactions after earnings calls. Our findings suggest that obstructing the flow of information leads to significantly lower cumulative abnormal stock returns and higher implied volatility. As both our method and glossary are free of financial context, we believe that the measure is applicable to other fields with a Q&A setup outside the contextual domain of financial earnings conference calls.
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Herding Behavior and Systemic Risk in Global Stock Markets
Iftekhar Hasan, Radu Tunaru, Davide Vioto
Journal of Empirical Finance,
September
2023
Abstract
This paper provides new evidence of herding due to non- and fundamental information in global equity markets. Using quantile regressions applied to daily data for 33 countries, we investigate herding during the Eurozone crisis, China’s market crash in 2015–2016, in the aftermath of the Brexit vote and during the Covid-19 Pandemic. We find significant evidence of herding driven by non-fundamental information in case of negative tail market conditions for most countries. This study also investigates the relationship between herding and systemic risk, suggesting that herding due to fundamentals increases when systemic risk increases more than when driven by non-fundamentals. Granger causality tests and Johansen’s vector error-correction model provide solid empirical evidence of a strong interrelationship between herding and systemic risk, entailing that herding behavior may be an ex-ante aspect of systemic risk, with a more relevant role played by herding based on fundamental information in increasing systemic risk.
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IWH-DPE Call for Applications – Fall 2024 Intake
IWH-DPE Call for Applications About the IWH Doctoral Programme in Economics The IWH Doctoral Programme in Economics (IWH-DPE) is a rigorous structured four-year PhD programme with…
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