Lagged accuracy in credit-risk measures
| dc.contributor.author | Abinzano Guillén, María Isabel | |
| dc.contributor.author | González Urteaga, Ana | |
| dc.contributor.author | Muga Caperos, Luis Fernando | |
| dc.contributor.author | Sánchez Alegría, Santiago | |
| dc.contributor.department | Institute for Advanced Research in Business and Economics - INARBE | en |
| dc.date.accessioned | 2022-05-19T10:41:06Z | |
| dc.date.available | 2024-06-01T23:00:09Z | |
| dc.date.issued | 2022 | |
| dc.description.abstract | This paper analyzes the magnitude (accuracy) and length (time) of the lag in the incorporation of new information in different measures of credit risk. The results, for US firms, show a lag for Altman’s Z accounting measure and credit rating. In contrast, market-based credit-risk measures such as CDSs and the Black-Scholes-Merton model show no lag. This paper also analyzes the determinants of the lags found showing the importance of the informativeness of CDSs in reducing the lag for all types of default events, and a negative relationship between accounting manipulation and the lag of Altman’s Z for severe default events. | en |
| dc.description.sponsorship | We gratefully acknowledge financial support from the Spanish Ministry of Science and Innovation (PID2019-104304GB-I00/AEI/10.13039/50110 0 011033). In addition, Ana González-Urteaga acknowledges financial support from the Ministry of Science, Innovation, and Universities through grant PGC2018-095072-B-I00. | en |
| dc.embargo.lift | 2024-06-01 | |
| dc.embargo.terms | 2024-06-01 | |
| dc.format.extent | 15 p. | |
| dc.format.mimetype | application/pdf | en |
| dc.identifier.doi | 10.1016/j.frl.2021.102653 | |
| dc.identifier.issn | 1544-6123 | |
| dc.identifier.uri | https://academica-e.unavarra.es/handle/2454/42980 | |
| dc.language.iso | eng | en |
| dc.publisher | Elsevier | en |
| dc.relation.ispartof | Finance Research Letters 47 (2022) 102653 | en |
| dc.relation.projectID | info:eu-repo/grantAgreement/AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2017-2020/PID2019-104304GB-I00/ES/ | |
| dc.relation.projectID | info:eu-repo/grantAgreement/AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2017-2020/PGC2018-095072-B-I00/ES/ | |
| dc.relation.publisherversion | https://doi.org/10.1016/j.frl.2021.102653 | |
| dc.rights | © 2021 Elsevier Inc. his manuscript version is made available under the CC-BY-NC-ND 4.0 | en |
| dc.rights.accessRights | info:eu-repo/semantics/openAccess | |
| dc.rights.uri | https://creativecommons.org/licenses/by-nc-nd/4.0/ | |
| dc.subject | Accruals | en |
| dc.subject | Accuracy | en |
| dc.subject | CDS informativeness | en |
| dc.subject | Credit-risk measures | en |
| dc.subject | Hard-to-value stocks | en |
| dc.subject | Lag | en |
| dc.title | Lagged accuracy in credit-risk measures | en |
| dc.type | info:eu-repo/semantics/article | |
| dc.type.version | info:eu-repo/semantics/acceptedVersion | |
| dspace.entity.type | Publication | |
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