Corporate Bond Pricing via Benchmark Combination Model

Research output: Working PapersPreprint

Abstract

This paper develops a benchmark combination model (BCM), which combines univariate-sorted basis portfolios using multiple characteristics, to perform asset evaluation. Under the non-arbitrage restriction, we estimate the common combination weights of BCM to minimize aggregate realized pricing errors. Using a long-span (45-year) sample of U.S. corporate bonds, we find BCM substantially outperforms standard factor models in pricing individual corporate bonds. BCM identifies important risk premia components, including credit rating, maturity, short-term reversal, momentum and variance. There is strong evidence of return predictability for these characteristic-sorted basis portfolios as well as high out-of-sample predictive power for individual bond returns.
Original languageEnglish
PublisherSocial Science Research Network (SSRN)
Publication statusOnline published - 12 Oct 2021

Bibliographical note

Research Unit(s) information for this publication is provided by the author(s) concerned.

Research Keywords

  • Characteristic-based benchmark
  • corporate bond pricing
  • forecast combination
  • machine learning
  • risk premia

Fingerprint

Dive into the research topics of 'Corporate Bond Pricing via Benchmark Combination Model'. Together they form a unique fingerprint.

Cite this