dc.contributor
Universitat Rovira i Virgili. Departament d'Economia
dc.contributor.author
Aslanidis, Nektarios,
dc.contributor.author
Christiansen, Charlotte
dc.contributor.author
Cipollini, Andrea
dc.date.accessioned
2018-03-09T13:49:58Z
dc.date.accessioned
2024-12-10T13:35:44Z
dc.date.available
2018-03-09T13:49:58Z
dc.date.available
2024-12-10T13:35:44Z
dc.date.created
2017-12-07
dc.identifier.uri
http://hdl.handle.net/2072/306546
dc.description.abstract
We predict bond betas conditioning on various macro-finance variables. We explore differences across long-term government bonds, investment grade corporate bonds, and
high yield corporate bonds. We conduct out-of-sample forecasting using the new approach of
combining explanatory variables through complete subset regressions (CSR). We consider the
robustness of CSR forecasts across the 1-month, 3-month, and 12-month forecasting horizon.
The CSR method performs well in predicting bond betas.
Keywords: bond betas; complete subset regressions; corporate bonds; government bonds;
macro-finance variables; model confidence set.
JEL Classifications: C22; C53; C55; G12.
eng
dc.publisher
Universitat Rovira i Virgili. Centre de Recerca en Economia Industrial i Economia Pública
dc.relation.ispartofseries
Documents de treball del Departament d'Economia;2018-03
dc.rights
L'accés als continguts d'aquest document queda condicionat a l'acceptació de les condicions d'ús establertes per la següent llicència Creative Commons: http://creativecommons.org/licenses/by-nc-nd/4.0/
dc.source
RECERCAT (Dipòsit de la Recerca de Catalunya)
dc.subject.other
Bons -- Models matemàtics
dc.title
Predicting Bond Betas using Macro-Finance Variables
dc.type
info:eu-repo/semantics/workingPaper
dc.rights.accessLevel
info:eu-repo/semantics/openAccess
