2021
DOI: 10.1108/raf-10-2020-0295
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The effect of credit rating downgrades along the supply chain

Abstract: Purpose This study aims to examine the information transfer effects of customers’ credit rating downgrades on supplier firms. Design/methodology/approach In this study, the authors use suppliers’ cumulative abnormal returns around customers’ credit rating downgrade events to identify how shocks to customer credit impact supplier equity prices. The authors also incorporate ordinary least squares and weighted least squares regressions regression analysis of the determinants of supplier market response to custo… Show more

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Cited by 4 publications
(4 citation statements)
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References 54 publications
(77 reference statements)
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“…Once the individual returns are estimated, we convert them into value-weighted countrywide portfolios. As mentioned before event studies have been extensively employed to assess the impact of changes in underlying factors like earnings uncertainty ( Wang, 2020 ), ( Chen et al., 2022 ) reduction in credit capacity ( Alldredge et al., 2022 ), and geopolitical risks ( Le et al., 2022 ; Theiri et al., 2022 ). To proxy market returns, the MSCI Euro index is considered.…”
Section: Research and Methodologymentioning
confidence: 99%
“…Once the individual returns are estimated, we convert them into value-weighted countrywide portfolios. As mentioned before event studies have been extensively employed to assess the impact of changes in underlying factors like earnings uncertainty ( Wang, 2020 ), ( Chen et al., 2022 ) reduction in credit capacity ( Alldredge et al., 2022 ), and geopolitical risks ( Le et al., 2022 ; Theiri et al., 2022 ). To proxy market returns, the MSCI Euro index is considered.…”
Section: Research and Methodologymentioning
confidence: 99%
“…Credit ratings reflect an independent opinion on the debt service capacity of an entity (Alldredge et al. , 2022; Li et al.…”
Section: Methodsmentioning
confidence: 99%
“…2.1.3 Credit ratings. Credit ratings reflect an independent opinion on the debt service capacity of an entity (Alldredge et al, 2022;Li et al, 2020;Yu et al, 2022). The rating agencies form this opinion based on many qualitative and quantitative factors from macro and microeconomic perspectives (White, 2013).…”
Section: Human Capital Efficiency Of Commercial Banksmentioning
confidence: 99%
“…Currently, supply chain finance credit risk prediction and evaluation methods include grey prediction model [8], linear regression model [9], support vector regression [10], machine learning methods [10], deep learning methods [11], etc. Literature [12] applies blockchain technology to the supply chain smart contract aspect and proposes a credit risk prediction method for supply chain finance based on grey theory; Literature [13] researches the method of combining blockchain technology with the actual needs of enterprises based on the underlying technology of Bitcoin and using the transparency of the transaction information; Literature [14] researches the supply chain architecture based on the blockchain technology, and proposes the supply chain process optimization method; Literature [15] proposed a financial credit risk prediction method based on improved machine learning method through the perspective of global supply chain product security and challenges; Literature [16] proposed blockchain-based encryption technology and studied the evaluation and analysis method of the corresponding technology; Literature [17] predicted the supply chain financial credit risk by analyzing the supply chain financial credit risk influencing factors and adopting the artificial neural network method to predict the supply chain finance credit risk and responds to enterprise demand in real time. According to the analysis of the above literature, the existing credit risk prediction methods of supply chain finance have the following defects:…”
Section: Introductionmentioning
confidence: 99%