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.

Aslanidis, N., Christiansen, C., Cipollini, A. (2019). Predicting bond betas using macro-finance variables. FINANCE RESEARCH LETTERS, 29, 193-199 [10.1016/j.frl.2018.07.007].

Predicting bond betas using macro-finance variables

Cipollini, Andrea
2019-01-01

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.
2019
Aslanidis, N., Christiansen, C., Cipollini, A. (2019). Predicting bond betas using macro-finance variables. FINANCE RESEARCH LETTERS, 29, 193-199 [10.1016/j.frl.2018.07.007].
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/10447/358861
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