Predicting bond betas using macro-finance variables

Andrea Cipollini, Charlotte Christiansen, Nektarios Aslanidis

Research output: Contribution to journalArticlepeer-review

7 Citations (Scopus)


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.
Original languageEnglish
Pages (from-to)193-199
Number of pages7
JournalFinance Research Letters
Publication statusPublished - 2019

All Science Journal Classification (ASJC) codes

  • Finance


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