On the dynamics of treasury bond yields: From term structure modelling to economic scenario generation

Yi Hong, Maochun Xu, Conghua Wen*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

Abstract

This study proposes an algorithmic framework that integrates the dynamic modelling of the term structure of treasury bond yields with the generation of market-consistent economic scenarios. The unscented Kalman filter (UKF) that works as a non-linear learning instrument for historical bond yields under the multi-factor models can facilitate the in-sample yield curve modelling, underpinned by statistical inferences, and further enhance the performance of the out-of-sample bond pricing and yield predictability. Moreover, market views that gauge the holistic assessments of macroeconomic prospects are incorporated into our framework. As such, the market-consistent economic scenarios are driven primarily by the dynamics of the term structure of bond yields and aggregate market sentiments among investors, offering a new instrument for interest rate risk management.

Original languageEnglish
Article number101542
JournalBritish Accounting Review
DOIs
Publication statusAccepted/In press - 2025

Keywords

  • Bias correction
  • Economic scenario generation
  • Multi-factor model
  • Term structure modelling
  • Unscented kalman filter (UKF)

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