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Predicting Bond Betas using Macro-Finance Variables

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  • Aslanidis, Nektarios,
  • Christiansen, Charlotte
  • Cipollini, Andrea
  • Bons -- Models matemàtics

Abstract

We predict bond betas conditioning on various 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 explanatory variables through complete subset regressions (CSR). We consider the robustness of CSR forecasts across the 1-month, 3-month, and 12-month forecasting horizon. The CSR method performs well in predicting bond betas. Keywords: bond betas; complete subset regressions; corporate bonds; government bonds; macro-finance variables; model confidence set. JEL Classifications: C22; C53; C55; G12.

Suggested Citation

  • Aslanidis, Nektarios, & Christiansen, Charlotte & Cipollini, Andrea & Bons -- Models matemàtics, 2018. "Predicting Bond Betas using Macro-Finance Variables," Working Papers 2072/306546, Universitat Rovira i Virgili, Department of Economics.
    • Handle: RePEc:urv:wpaper:2072/306546
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    Cited by:

    1. Ermolov, Andrey, 2022. "Time-varying risk of nominal bonds: How important are macroeconomic shocks?," Journal of Financial Economics, Elsevier, vol. 145(1), pages 1-28.
    2. Cheng, Tingting & Jiang, Shan & Zhao, Albert Bo & Jia, Zhimin, 2023. "Complete subset averaging methods in corporate bond return prediction," Finance Research Letters, Elsevier, vol. 54(C).

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    More about this item

    Keywords

    Bons -- Models matemàtics; 336 - Finances. Banca. Moneda. Borsa;

    JEL classification:

    • G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates
    • G14 - Financial Economics - - General Financial Markets - - - Information and Market Efficiency; Event Studies; Insider Trading

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