Factors influencing the European bank’s probability of default: An application of SYMBOL methodology

Parrado-Martínez, Purificación; Gómez-Fernández-Aguado, Pilar; Ureña, Antonio Partal

doi:10.1016/j.intfin.2019.04.003

Cited by 14 publications

(15 citation statements)

References 60 publications

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“…and st term funding Equity/deposits and short-term funding Climenta et al [ 56 ] and Distinguin et al [ 17 ] Equity-to-liabilities Equity/liabilities Climenta et al [ 56 ] and Distinguin et al [ 17 ] Capital funds-to-assets (Equity + debt)/total assets Climenta et al [ 56 ] and Distinguin et al [ 17 ] Capital funds-to-gross loans* (Equity + debt)/gross loans Distinguin et al [ 17 ] Panel B: Asset quality variables Impaired loans-to-equity Impaired loans/equity Betz et al [ 13 ] Non perf. loans-to-gross loans Non-performing loans/total gross loans Chiaramonte and Casu [ 14 ], Parrado-Martinez et al [ 59 ] and Poghosyan and Cihak [ 7 ] Loan loss res.-to- non perf. loans Loans loss reserves/non-performing loans Ötker-Robe and Podpiera [ 33 ] Coverage ratio* Loans loss reserves/impaired loans Betz et al [ 13 ] and Parrado-Martinez et al [ 59 ] Loan loss res.-to-gross loans Loans loss reserves/gross loans Climenta et al [ 56 ], Cole and White [ 9 ] and Distinguin et al [ 17 ] Loan loss res.-to- total loans* Loans loss reserves/total loans Arena [ 12 ], Ötker-Robe and Podpi...…”

Section: Methodsmentioning

confidence: 99%

“…loans Loans loss reserves/non-performing loans Ötker-Robe and Podpiera [ 33 ] Coverage ratio* Loans loss reserves/impaired loans Betz et al [ 13 ] and Parrado-Martinez et al [ 59 ] Loan loss res.-to-gross loans Loans loss reserves/gross loans Climenta et al [ 56 ], Cole and White [ 9 ] and Distinguin et al [ 17 ] Loan loss res.-to- total loans* Loans loss reserves/total loans Arena [ 12 ], Ötker-Robe and Podpiera [ 33 ] and Sironi [ 15 ] Loan loss res.-to-assets* Loan-loss-reserves/assets Avino et al [ 60 ], Betz et al [ 13 ], Cole and White [ 9 ], Curry et al [ 3 ] and Milne [ 61 ] Loan loss res.-to-interest revenue Loan loss reserves/net interest revenue Climenta et al [ 56 ] and Distinguin et al [ 17 ] ROA Net income/total assets Betz et al [ 13 ], Cleary and Hebb [ 23 ], Cole and White [ 9 ], Curry et al [ 3 ], Distinguin et al [ 17 ], Jing and Fang [ 57 ], Ötker-Robe and Podpiera [ 33 ], Parrado-Martinez et al [ 59 ] and Sironi [ 15 ] ROAA Net income/average assets Chiaramonte and Casu [ 14 ], Climenta et al [ 5...…”

Section: Methodsmentioning

confidence: 99%

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Reassessing bank monitoring models: an empirical analysis of the value of market signals in the period 2008–2020

2022

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One of the major goals of bank supervisors is to predict bank distress events. As the environment changes, it is crucial to reassess and improve the models used in monitoring banks. The financial soundness of banks is traditionally assessed based on accounting ratios. However, the incorporation of market information in these models may significantly improve its ability to predict bank distress. The present paper has two main objectives, the first is to assess if market information adds value to accounting-based monitoring models when the purpose is to detect bank distress situations. Further, it also seeks to understand if the predictive power of market signals increased with transparency requirements. To accomplish this purpose, a total of 81 distress events from a sample of 248 European banks between 2008 and 2020 were analyzed. First, a logit univariate analysis was used to evaluate the relevance of each accounting and market variable. Then, the optimal multivariate accounting-based model to predict distress events was constructed using a stepwise approach. Finally, the previous model was extended to include the relevant market variables. The results support the use of market variables in bank monitoring models. Further, the present study provides evidence that the predictive power of market variables increased after the strengthening of the information requirements set by the Basel agreements. It can be concluded that the results support the use of market information for banking supervisory purposes, especially, in transparent markets. Supplementary Information The online version contains supplementary material available at 10.1057/s41261-022-00194-4.

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Section: Methodsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

Reassessing bank monitoring models: an empirical analysis of the value of market signals in the period 2008–2020

2022

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“…In line with prior literature (Dong, Girardone, & Kuo, 2017), the authors adopt as proxies of loan portfolio risk: the nonperforming loans to gross loans (NPL_ratio), the loan loss reserves to gross loans (LLR_ratio), and the impaired loans to gross loans (Impaired_ratio). Specifically, the NPL_ratio has been used as a measurement of the strength of a bank (Festic, Kavkler, & Repina, 2011) since it reflects the quality of the loan portfolio (Parrado‐Martinez, Gòmez‐Fernàndez‐Aguado, & Partal‐Urena, 2019). Under general classification, loans are divided into five categories: standard, special mention, substandard, doubtful, and loss.…”

Section: Methodsmentioning

confidence: 99%

Bank Risk Appetite Communication and Risk Taking: The Key Role of Integrated Reports

2021

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This article investigates whether qualitative information provided by banks about risk appetite (RA) sheds substantive insight on their effective risk taking (RT) and whether this latter in turn affects RA disclosure, as well as the role played by specific types of banks’ reports (i.e., integrated report, annual report, Pillar 3 report) on such relations. Using a sample of 134 reports representing 52 banks, a generalized structural equation model is applied. The article hypothesizes and empirically finds a reciprocal relation between RA disclosure and banks’ RT. More specifically, in line with agency theory, the analysis displays a predominance of the inverse relation according to which banks showing higher RT provide greater disclosure. In addition, RT is found to play a mediator role between the adoption of a specific type of report—the integrated report—and RA disclosure, independently of the context in which the banks operate. Results also highlight that RT in banks adopting an integrated report is lower than the one of matched banks. Overall, this study extends risk science by complementing the literature stream on banks’ accounting discretion and risk disclosure, supporting the impact of market discipline in promoting new forms of corporate reporting. Results indeed emphasize the key role of integrated reporting on RT, suggesting that integrated logic should be strengthened by policy makers to curb banks’ excessive RT and leading them to provide substantive disclosure.

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“…Lender Specific Islamic vs Conventional (Ari et al, 2021;Aysan et al, 2016;Choudhary & Jain, 2021;Fonseca & González, 2008;Ghosh, 2015;Hegde & Kozlowski, 2021;Howells & Rogner, 2014;Lafuente et al, 2019;P.-L. Lee et al, 2022;Palvia et al, 2020;Parrado-Martínez et al, 2019;Puri et al, 2017;Soenen & Vander Vennet, 2022;Vonnák, 2018;Wasiaturrahma et al, 2020;Wengerek et al, 2022;Widodo et al, 2022) (Alandejani & Asutay, 2017;Baele et al, 2014;Bekele et al, 2016;Disli et al, 2022;Riahi, 2019;Saeed & Izzeldin, 2016;Saif-Alyousfi et al, 2018) As indicated earlier, fifty-two (52) articles were synthesized to engender clarity in the literature and to provide more understanding. The aggregation of the first-order and second-order codes established that most of the articles studied addressed the demand side of the financial market.…”

Section: Borrower Specificmentioning

confidence: 99%

Determinants of Non-Performing Loans Between Islamic And Conventional Banks: A Systematic Literature Review

Almuraikhi¹

2022

jeb

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This article conducts a systematic literature review of 52 papers on the determinants of non-performing loans (NPL) published for 2006-2022 in peer-reviewed journals. This paper adds to the development of this emerging field of systematic review in non-medical field settings by mapping existing research to inform future research exploits. This study synthesizes NPL studies by applying the systematic review methodology. The data synthesis is done through first and second-level codes. The first level codes group studies according to bank-specific, borrower-specific and comparative (Islamic vs conventional bank types). The literature is conscientiously analyzed through 13 subcategories using an open coding process. The literature synthesis shows that borrower-specific factors that may determine NPL include borrower profile, internal factors, external factors, and social issues. Also, the bank-specific factors that may influence NPL growth include economic conditions, management competence, profit maximization, and information economics. The findings highlight that the way borrower profiles, banks-specific factors and macroeconomic factors interact to influence NPL still needs more understanding. Further, Islamic banks and conventional banks seem to behave similarly regarding many bank-specific and macroeconomic factors even though the profit and loss sharing contract used in Islamic banks was deemed to moderate NPL positively. But the borrower-specific factors' interaction with bank-specific and macroeconomic factors of Islamic banks clients remains unclear. This highlights an important research gap in understanding the behavior of Islamic bank borrowers towards NPL prediction.

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Factors influencing the European bank’s probability of default: An application of SYMBOL methodology

Cited by 14 publications

References 60 publications

Reassessing bank monitoring models: an empirical analysis of the value of market signals in the period 2008–2020

Reassessing bank monitoring models: an empirical analysis of the value of market signals in the period 2008–2020

Bank Risk Appetite Communication and Risk Taking: The Key Role of Integrated Reports

Determinants of Non-Performing Loans Between Islamic And Conventional Banks: A Systematic Literature Review

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