We develop a conditional factor model for the term structure of treasury bonds, which unifies non parametric curve estimation with cross-sectional asset pricing. Our factors correspond to the optimal non-parametric basis functions spanning the discount curve. They are investable portfolios...

We propose a new framework to explain the factor structure in the full cross section of Treasury bond returns. Our method unifies non-parametric curve estimation with cross-sectional factor modeling. We identify smoothness as a fundamental principle of the term structure of returns. Our 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 in reproducing Hilbert spaces with an economically motivated smoothness reward. We provide a closed-form...

This study used the GT NEMS model to analyze how the proposed federal regulation on carbon emissions will impact investments in the U.S. electricity generating capacity at the federal and Census Division level for 2016-2030. Results show that in order to reduce emissions by 32% by 2030,...

This study used the GT NEMS model to analyze how the proposed federal regulation on carbon emissions will impact investments in the U.S. electricity generating capacity at the federal and Census Division level for 2016-2030. Results show that in order to reduce emissions by 32% by 2030,...

This study used the GT NEMS model to analyze how the proposed federal regulation on carbon emissions will impact investments in the U.S. electricity generating capacity at the federal and Census Division level for 2016-2030. Results show that in order to reduce emissions by 32% by 2030,...