Multiple Yield Curve Modeling and Forecasting using Deep Learning

This manuscript introduces deep learning models that simultaneously describe the dynamics of several yield curves. We aim to learn the dependence structure among the different yield curves induced by the globalization of financial markets and exploit it to produce more accurate forecasts. By combining the self-attention mechanism and nonparametric quantile regression, our model generates both point and interval forecasts of future yields. The architecture is designed to avoid quantile crossing issues affecting multiple quantile regression models. Numerical experiments conducted on …

aim attention cs.lg deep learning dynamics exploit financial financial markets forecasting globalization learn markets modeling multiple quantile regression self-attention stat.ml yield curve