Advanced

Predicting bond betas using macro-finance variables

Aslanidis, Nektarios; Christiansen, Charlotte LU and Cipollini, Andrea (2019) In Finance Research Letters 29. p.193-199
Abstract

We predict bond betas conditioning on a number of 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 predictor variables through complete subset regressions (CSR). We consider the robustness of CSR forecasts across the 1-month, 3-month, and 12-month forecasting horizons. The CSR method performs well in predicting bond betas.

Please use this url to cite or link to this publication:
author
organization
publishing date
type
Contribution to journal
publication status
published
subject
keywords
Bond betas, Complete subset regressions, Corporate bonds, Government bonds, Macro-finance variables, Model confidence set
in
Finance Research Letters
volume
29
pages
193 - 199
publisher
Elsevier
external identifiers
  • scopus:85051543474
ISSN
1544-6123
DOI
10.1016/j.frl.2018.07.007
language
English
LU publication?
yes
id
4b143ad7-4882-45ad-83c0-5f3e8d6b8b4c
date added to LUP
2018-09-13 13:03:16
date last changed
2019-09-17 04:38:33
@article{4b143ad7-4882-45ad-83c0-5f3e8d6b8b4c,
  abstract     = {<p>We predict bond betas conditioning on a number of 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 predictor variables through complete subset regressions (CSR). We consider the robustness of CSR forecasts across the 1-month, 3-month, and 12-month forecasting horizons. The CSR method performs well in predicting bond betas.</p>},
  author       = {Aslanidis, Nektarios and Christiansen, Charlotte and Cipollini, Andrea},
  issn         = {1544-6123},
  keyword      = {Bond betas,Complete subset regressions,Corporate bonds,Government bonds,Macro-finance variables,Model confidence set},
  language     = {eng},
  pages        = {193--199},
  publisher    = {Elsevier},
  series       = {Finance Research Letters},
  title        = {Predicting bond betas using macro-finance variables},
  url          = {http://dx.doi.org/10.1016/j.frl.2018.07.007},
  volume       = {29},
  year         = {2019},
}