6533b824fe1ef96bd12801ab
RESEARCH PRODUCT
Predicting bond betas using macro-finance variables
Andrea CipolliniAndrea CipolliniCharlotte ChristiansenNektarios Aslanidissubject
Government bondsYield (finance)Complete subset regressionsPredictor variablesModel confidence set0502 economics and businessEconometricsEconomicsCapital asset pricing model050207 economicsMacroRobustness (economics)FinanceBond betas Complete subset regressionsCorporate bondsGovernment bondsMacro-finance variablesModel confidence set050208 financebusiness.industryBond05 social sciencesInvestment (macroeconomics)Macro-finance variablesBond market indexGovernment (linguistics)Corporate social responsibilityBond betasBusinessCorporate bondsFinancedescription
We conduct in-sample and out-of-sample forecasting using the new approach of combining explanatory variables through complete subset regressions (CSR). We predict bond CAPM betas and bond returns conditioning on various macro-finance variables. We explore differences across long-term government bonds, investment grade corporate bonds, and high-yield corporate bonds. The CSR method performs well in predicting bond betas, especially in-sample, and, mainly high-yield bond betas when the focus is out-of-sample. Bond returns are less predictable than bond betas.
| year | journal | country | edition | language |
|---|---|---|---|---|
| 2019-06-01 |