Affiliation:
1. School of Economics and Management Nanjing University of Science and Technology Nanjing China
2. School of Economics Qingdao University Qingdao China
3. Adnan Kassar School of Business Lebanese American University Beirut Lebanon
Abstract
AbstractThis paper uses the default return spread (DFR) to predict crude oil price returns over the period January 1986 through December 2020. Results of in‐sample and out‐of‐sample analyses show that the DFR can predict oil price returns and significantly outperform the benchmark and other competing variables. In an asset allocation exercise, a mean–variance investor can obtain considerable certainty equivalent return (CER) gains based on the return forecasts of DFR relative to the benchmark. We also perform a series of robustness tests to confirm our previous conclusion. We further investigate the source of the DFR's predictive ability from oil market sentiment, in which we provide some theoretical basis to explain.
Funder
National Natural Science Foundation of China
Subject
Management Science and Operations Research,Statistics, Probability and Uncertainty,Strategy and Management,Computer Science Applications,Modeling and Simulation,Economics and Econometrics
Cited by
7 articles.
订阅此论文施引文献
订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献