6533b824fe1ef96bd12801ab

RESEARCH PRODUCT

Predicting bond betas using macro-finance variables

Andrea CipolliniAndrea CipolliniCharlotte ChristiansenNektarios Aslanidis

subject

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 bondsFinance

description

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.

10.1016/j.frl.2018.07.007https://pure.au.dk/portal/da/publications/predicting-bond-betas-using-macrofinance-variables(3eecf7fa-b931-4861-af88-51c69a686889).html