Calibration of the Hull-White one-factor short-rate model on €STR data, and multi-method swaption pricing under three equivalent measures.
This project implements the full pipeline from model calibration to derivative pricing within the Hull-White (HW) framework:
-
Calibration of the HW parameters
$(a, \sigma)$ from historical €STR data under the real-world measure$\mathbb{P}$ , using two methods: AR(1) regression and Maximum Likelihood Estimation (MLE). -
Yield curve fitting via a Nelson-Siegel parametrization to extract the initial term structure
$\theta(t)$ . -
Swaption pricing under three equivalent measures — risk-neutral
$\mathbb{Q}$ , forward measure, and annuity measure — using Monte Carlo simulations and a Trinomial Tree. - Convergence & sensitivity analysis of both numerical methods.
The Hull-White one-factor model under the risk-neutral measure
-
$a$ : mean-reversion speed (constant) -
$\sigma$ : volatility (constant) -
$\theta(t)$ : time-dependent drift calibrated to fit the initial yield curve
| Method | Swaption Price |
|---|---|
| Monte Carlo — Risk-neutral |
9.887 % |
| Monte Carlo — Forward measure | 9.887 % |
| Monte Carlo — Annuity measure | 9.886 % |
| Trinomial Tree | 9.888 % |
All four methods converge to ~9.89%, confirming the consistency of the implementation across measures and numerical schemes.
rates-models/
├── notebooks/
│ └── hull_white_swaption_pricing.ipynb # Full pipeline: calibration → pricing
├── data/
│ └── ESTR.csv # ECB Euro Short-Term Rate (daily)
└── README.md
Prerequisites
pip install numpy pandas scipy matplotlibRun the notebook
jupyter notebook notebooks/hull_white_swaption_pricing.ipynbThe notebook reads data from
../data/ESTR.csv— keep the folder structure intact.
- Hull, J. & White, A. (1990). Pricing Interest-Rate Derivative Securities. The Review of Financial Studies.
- Brigo, D. & Mercurio, F. (2006). Interest Rate Models — Theory and Practice. Springer.
- ECB Statistical Data Warehouse — Euro Short-Term Rate (€STR):
EST.B.EU000A2X2A25.WT