Predicting Bond Betas using Macro-Finance Variables

Publikation: Working paperForskning

Dokumenter

  • rp17_01

    Forlagets udgivne version, 410 KB, PDF-dokument

  • Nektarios Aslanidis, University Rovira Virgili, Spanien
  • Charlotte Christiansen
  • Andrea Cipollini, University of Palermo, Italien
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-fi…nance 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.
OriginalsprogEngelsk
UdgivelsesstedAarhus
UdgiverInstitut for Økonomi, Aarhus Universitet
Antal sider32
StatusUdgivet - 11 jan. 2017
SerietitelCREATES Research Papers
Nummer2017-01

    Forskningsområder

  • bond betas, complete subset regressions, corporate bonds, macro-…finance variables, model confi…dence set, risk-return trade-off

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