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.contributor.author |
|
dc.date.accessioned |
2018-03-09T13:49:58Z |
dc.date.available |
2018-03-09T13:49:58Z |
dc.date.created |
2017-12-07 |
dc.date.issued |
2018 |
dc.identifier.uri |
http://hdl.handle.net/2072/306546 |
dc.format.extent |
14 p. |
dc.language.iso |
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.subject.udc |
336 - Finances. Banca. Moneda. Borsa |
dc.embargo.terms |
cap |
dc.rights.accessLevel |
info:eu-repo/semantics/openAccess |
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. |