Bond Risk Premia with Machine Learning∗

By Daniele Bianchi, M. Büchner, Andrea Tamoni. 2018

Subfields: Statistics and Probability, Economics & Operations Research

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Statistics and Probability

1. Jason Zhu
2. Luyang Chen
3. A. Ozbayoglu
4. Omer Berat Sezer
5. M. Ugur Gudelek
6. Markus Pelger
7. Ruoxuan Xiong

In Economics & Operations Research

1. A. Ozbayoglu
2. M. Ugur Gudelek
3. Jason Zhu
4. Luyang Chen
5. Omer Berat Sezer
6. Markus Pelger

Citations in the corpus

• Financial Time Series Forecasting with Deep Learning : A Systematic Literature Review: 2005-2019 (2019, methodology): “In one study [166], excess bond return was predicted using several ML models including RF, AE and PCA network and a 2-3-4-layer DFNN.”
• Deep Learning in Asset Pricing (2019, methodology): “Bianchi et al. (2019) provide a comparison of machine learning method for predicting bond returns in the spirit of Gu et al.”