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Spurious Cross-Sectional Dependence in Credit Spread Changes

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dc.contributor.authorJaskowski, Marcin
dc.contributor.authorMcAleer, Michael
dc.date.accessioned2023-06-17T17:53:46Z
dc.date.available2023-06-17T17:53:46Z
dc.date.issued2018-09
dc.descriptionAcknowledgments: For financial and research support, the second author wishes to thank the Australian Research Council and the Ministry of Science and Technology (MOST), Taiwan.
dc.description.abstractIn order to understand the lingering credit risk puzzle and the apparent segmentation of the stock market from credit markets, we need to be able to assess the strength of the cross-sectional dependence in credit spreads. This turns out to be a non-trivial task due to the extreme data sparsity that is typical for any panel of credit spreads that is extracted from corporate bond transactions. The problem of data sparsity has led to some erroneous conclusions in the literature, including inferences that have been drawn from spurious cross-sectional dependence in credit spread changes. Understanding the pitfalls leads to a new and improved estimator of the latent factor in credit spread changes and its characteristics.
dc.description.facultyFac. de Ciencias Económicas y Empresariales
dc.description.facultyInstituto Complutense de Análisis Económico (ICAE)
dc.description.refereedTRUE
dc.description.sponsorshipthe Australian Research Council
dc.description.sponsorshipthe Ministry of Science and Technology (MOST), Taiwan.
dc.description.statusunpub
dc.eprint.idhttps://eprints.ucm.es/id/eprint/49149
dc.identifier.issn2341-2356
dc.identifier.officialurlhttps://www.ucm.es/icae/working-papers
dc.identifier.relatedurlhttps://www.ucm.es/icae
dc.identifier.urihttps://hdl.handle.net/20.500.14352/17438
dc.issue.number21
dc.language.isoeng
dc.page.total31
dc.relation.ispartofseriesDocumentos de Trabajo del Instituto Complutense de Análisis Económico (ICAE)
dc.rights.accessRightsopen access
dc.subject.jelG12
dc.subject.jelG13
dc.subject.jelG17
dc.subject.jelE43
dc.subject.keywordCredit spread puzzle
dc.subject.keywordMarket segmentation
dc.subject.keywordLatent factors
dc.subject.keywordSpurious cross-sectional dependence.
dc.subject.ucmEconometría (Economía)
dc.subject.ucmFinanzas
dc.subject.unesco5302 Econometría
dc.titleSpurious Cross-Sectional Dependence in Credit Spread Changes
dc.typetechnical report
dc.volume.number2018
dcterms.referencesAvramov, Doron, Gergana Jostova, and Alexander Philipov, 2007, Understanding changes in corporate credit spreads, Financial Analysts Journal, 63, 90-105. Castagnetti, Carolina, and Eduardo Rossi, 2013, Euro corporate bond risk factors, Journal of Applied Econometrics, 28, 372-391. Collin-Dufresne, Pierre, Robert S Goldstein, and J Spencer Martin, 2001, The determinants of credit spread changes, Journal of Finance, 56, 2177-2207. Cremers, Martijn, Joost Driessen, Pascal Maenhout, and David Weinbaum, 2008, Individual stock-option prices and credit spreads, Journal of Banking and Finance, 32, 2706-2715. Ericsson, Jan, Kris Jacobs, and Rodolfo Oviedo, 2009, The determinants of credit default swap premia, Journal of Financial and Quantitative Analysis, 44, 109-132. Huang, Jing-Zhi, and Ming Huang, 2012, How much of the corporate-treasury yield spread is due to credit risk?, Review of Asset Pricing Studies, 2, 153-202. Pesaran, M Hashem, 2006, Estimation and inference in large heterogeneous panels with a multifactor error structure, Econometrica, 74, 967-1012. Pesaran, M Hashem, 2015,Testing weak cross-sectional dependence in large panels, Econometric Reviews, 34, 1089-1117. Porta, Josep, Jakob Verbeek, and Ben Krose, 2005, Active appearance-based robot localization using stereo vision, Autonomous Robots, 18, 59-80. Schaefer, Stephen M., and Ilya A. Strebulaev, 2008, Structural models of credit risk are useful: Evidence from hedge ratios on corporate bonds, Journal of Financial Economics, 90, 1-19.
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