U.S. Treasury Discount Bond Database
Discount Bond Database
This reference dataset for treasury yields is based on the method in our paper "Stripping the Discount Curve - a Robust Machine Learning Approach". We introduce a robust, flexible and easy-to-implement method for estimating the yield curve from Treasury securities. This method is non-parametric and optimally learns basis functions with an economically motivated smoothness reward. We show in an extensive empirical study on daily U.S. Treasury securities, that our method strongly dominates all parametric and non-parametric benchmarks. Our method 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.
The reference dataset for discount bond returns and factors is based on our paper "Shrinking the Term Structure". We introduce a conditional factor model for the term structure of treasury bonds, which unifies non-parametric curve estimation with cross-sectional asset pricing. Our robust, flexible and easy-to-implement method learns the discount bond excess return curve directly from observed returns of treasury securities. This curve lies in a reproducing kernel Hilbert space, which is derived from economic first principles, and optimally trades off smoothness against return fitting. We show that a low dimensional factor model arises because a sparse set of basis functions spans the estimated discount bond excess return curves. The estimated factors are investable portfolios of traded assets, which replicate the full term structure and are sufficient to hedge against interest rate changes. In an extensive empirical study on U.S. Treasuries, we show that the discount bond excess return curve is well explained by four factors, which capture polynomial shapes of increasing order and are necessary to explain the term structure premium. The cash flows of coupon bonds fully explain the factor exposure, and play the same role as firm characteristics in equity modeling. In this sense, ``cash flows are covariances''. We introduce a new measure for the time-varying complexity of bond markets based on the exposure to higher-order factors, and show that changes in market complexity affect the term structure premium.
The data is updated regularly. Last update: September 7, 2023.
Discount bond returns
Term structure factors
Bond Market Condition Measures
This reference dataset is the result of the research of Damir Filipović, Markus Pelger and Ye Ye.