Studies of bond return predictability find a puzzling disparity between strong statistical
evidence of return predictability and the failure to convert return forecasts into economic …

This paper studies whether the evident statistical predictability of bond risk premia translates
into economic gains for investors. We propose a novel estimation strategy for affine term …

A previous literature has documented that bond returns are predicted by macroeconomic
information not contained in yields contemporaneously. That literature has mostly relied on …

This article investigates the out-of-sample predictability of bond excess returns. We assess
the economic value of the forecasting ability of empirical models based on long-term forward …

Using a comprehensive return data set and an array of 27 macroeconomic, stock, and bond
predictors, we find that corporate bond returns are highly predictable based on an iterated …

We investigate the return predictability of corporate bonds using big data and machine
learning. We find that machine learning models substantially improve the out-of-sample …

We show that machine learning methods, in particular, extreme trees and neural networks
(NNs), provide strong statistical evidence in favor of bond return predictability. NN forecasts …

Are there important cyclical fluctuations in bond market premiums and, if so, with what
macroeconomic aggregates do these premiums vary? We use the methodology of dynamic …

We show that bond risk premia rise with uncertainty about expected inflation and fall with
uncertainty about expected growth; the magnitude of return predictability using these …

In this note we revisit the empirical results in after correcting for using information not
available at the time the forecast was made. Although we note a decrease in out-of-sample …