A Sinusoidal Hull-White Model for Interest Rate Dynamics: Capturing Long-Term Periodicity in U.S. Treasury Yields
First published: 2025
Brief summary
Extends the standard Hull-White interest rate model with a sinusoidal, time-varying mean reversion term calibrated to a 22-year cycle identified via Fourier Transform analysis, built on earlier spectral findings of 5-30 year Treasury yield periodicities.
Article
A Sinusoidal Hull-White Model for Interest Rate Dynamics: Capturing Long-Term Periodicity in U.S. Treasury Yields is a preprint published by arXiv in 2025. It extends the standard Hull-White interest rate model with a sinusoidal, time-varying mean reversion term calibrated to a 22-year cycle identified via Fourier Transform analysis, built on earlier spectral findings of 5-30 year Treasury yield periodicities.
The analysis focuses on 22-year cycle (fitted). It also considers cites Gallant & Tauchen 1996 spectral analysis finding 5-20 year cycles, and Krichene 2006 Fourier analysis finding 10-30 year cycles in Treasury yields. The data source is daily US Treasury yield curves (FRED), 1990-2022. This gives the cycle claim a specific numerical and evidential setting rather than presenting periodicity only as a visual impression.
The article reports the following result: Gallant and Tauchen (1996) apply spectral analysis to U.S. Treasury yields, identifying periodic components with cycles of 5 to 20 years; more recently, Krichene (2006) employs Fourier Transform techniques to detect long-term cycles, finding evidence of 10- to 30-year periodicities. The interpretation is strongest when inflation regimes, monetary-policy changes, non-stationarity and out-of-sample performance are considered.
For cycles researchers, the article brings together hull-white model, treasury yields, 22-year cycle, fourier analysis. It is relevant to interest-rate cycle research because yield movements combine policy regimes, inflation dynamics, business cycles and long-frequency components.
Because it is a preprint, the work should be read alongside later peer-reviewed publications and independent replications. It remains useful because the proposed cycle, dataset and analytical approach are stated clearly enough to be scrutinised.
Source details and credits
- Source / publisher: arXiv
- Source type: Preprint
- URL type: PDF
- Credits: arXiv
- URL: https://arxiv.org/pdf/2506.06317