Bond Risk Premia with Machine Learning

84 Pages Posted: 26 Aug 2018 Last revised: 10 Feb 2020

See all articles by Daniele Bianchi

Daniele Bianchi

School of Economics and Finance, Queen Mary University of London

Matthias Büchner

University of Warwick - Finance Group

Andrea Tamoni

Rutgers, The State University of New Jersey - Rutgers Business School at Newark & New Brunswick

Date Written: February 7, 2020

Abstract

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 based on macroeconomic and yield information translate into economic gains that are larger than those ob- tained using yields alone. Interestingly, the nature of unspanned factors changes along the yield curve: stock and labor market related variables are more relevant for short-term maturities, whereas output and income variables matter more for longer maturities. Finally, NN forecasts correlate with proxies for time-varying risk aversion and uncertainty, lending support to models featuring both of these channels.

Keywords: Machine Learning, Ensembled Networks, Forecasting, Bond Return Predictability, Em- pirical Asset Pricing

JEL Classification: C38, C45, C53, E43, G12, G17

Suggested Citation

Bianchi, Daniele and Büchner, Matthias and Tamoni, Andrea, Bond Risk Premia with Machine Learning (February 7, 2020). WBS Finance Group Research Paper No. 252. Available at SSRN: https://ssrn.com/abstract=3232721 or http://dx.doi.org/10.2139/ssrn.3232721

Daniele Bianchi (Contact Author)

School of Economics and Finance, Queen Mary University of London ( email )

Mile End Rd
Mile End Road
London, London E1 4NS
United Kingdom

HOME PAGE: http://whitesphd.com

Matthias Büchner

University of Warwick - Finance Group ( email )

Gibbet Hill Rd
Coventry, CV4 7AL
Great Britain

HOME PAGE: http://mbuechner.com

Andrea Tamoni

Rutgers, The State University of New Jersey - Rutgers Business School at Newark & New Brunswick ( email )

1 Washington Park
Newark, NJ 07102
United States

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