 Macroeconomic variable selection for creditor recovery ratesAbdolreza Nazemi and Frank Fabozzi (frank.fabozzi@edhec.edu) Journal of Banking & Finance, 2018, vol. 89, issue C, 14-25 Abstract: We study the relationship between U.S. corporate bond recovery rates and macroeconomic variables used in the credit risk literature. The least absolute shrinkage and selection operator (LASSO) is used in selecting macroeconomic variables. The LASSO-selected macroeconomic variables are considered to be explanatory variables in ordinary least squares regressions, bootstrap aggregating (bagging), regression trees, boosting, LASSO, ridge regression and support vector regression techniques. We compare the out-of-sample predictive power of two types of models (LASSO-selected models with models that add principal components derived from 179 macroeconomic variables as explanatory variables). We find the recovery models with LASSO-selected macroeconomic variables outperform suggested models in the literature. Keywords: Macroeconomic variables; Least absolute shrinkage and selection operator (LASSO); Corporate bond; Recovery rates; Credit risk (search for similar items in EconPapers) Downloads: (external link) Related works: Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text Persistent link: https://EconPapers.repec.org/RePEc:eee:jbfina:v:89:y:2018:i:c:p:14-25 DOI: 10.1016/j.jbankfin.2018.01.006 Access Statistics for this article Journal of Banking & Finance is currently edited by Ike Mathur More articles in Journal of Banking & Finance from Elsevier |
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