“SWAPTION PRICING USING HULL-WHITE MODELS: A CASE STUDY”

Pricing models for interest rate derivatives have been object of discussion among several financial engineers and mathematicians. The complex nature of these financial securities is strictly related to the evolution of the short-term rate and market volatility risk, which can be incorporated into pricing models through the estimation of one or more factors of uncertainty. Among all different types of interest rate derivatives, this thesis investigates the pricing of options on an Interest-Rate-Swaps (IRS), commonly known as swaptions, computed under Hull-White one-factor and two-factor models. Using a dataset spanning over ten years for all necessary inputs, the analysis bridges the gap between the theoretical modeling and the real-world application, by executing calibration, Monte Carlo forecasting and Value-at risk computations with backtesting in MATLAB for both models. The purpose of this research is to compare and discuss the main differences between the one-factor and two-factor Hull-White pricing models, with a focus on their practical implications.