Predicting bond betas using macro-finance variables

Forskningsoutput: TidskriftsbidragArtikel i vetenskaplig tidskrift

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.

Detaljer

Författare
  • Nektarios Aslanidis
  • Charlotte Christiansen
  • Andrea Cipollini
Enheter & grupper
Externa organisationer
  • Rovira i Virgili University (URV)
  • Aarhus University
  • University of Palermo
Forskningsområden

Ämnesklassifikation (UKÄ) – OBLIGATORISK

  • Nationalekonomi

Nyckelord

Originalspråkengelska
Sidor (från-till)193-199
TidskriftFinance Research Letters
Volym29
Tidigt onlinedatum2018 jul 30
StatusPublished - 2019
PublikationskategoriForskning
Peer review utfördJa