Stripping the Discount Curve—A Robust Machine Learning Approach
Abstract
We introduce a robust, flexible, and easy-to-implement method for estimating the yield curve from treasury securities. Our nonparametric method learns the discount curve in a function space that we motivate by economic principles. We show in an extensive empirical study on U.S. Treasury securities that our method strongly dominates all parametric and nonparametric benchmarks. It achieves substantially smaller out-of-sample yield and pricing errors while being robust to outliers and data selection choices. We attribute the superior performance to the optimal trade-off between flexibility and smoothness, which positions our method as the new standard for yield curve estimation.
This paper was accepted by Agostino Capponi, finance.
Supplemental Material: The data files are available at https://doi.org/10.1287/mnsc.2023.01401.
