{"title":"Forecasting crude oil prices: Does global financial uncertainty matter?","authors":"Yong Ma , Shuaibing Li , Mingtao Zhou","doi":"10.1016/j.iref.2024.103723","DOIUrl":null,"url":null,"abstract":"<div><div>In this paper, we introduce an informative uncertainty measure, global financial uncertainty (GFU), for the prediction of crude oil price returns. We find that GFU exhibits significant and remarkable forecasting power for crude oil price returns both in- and out-of-sample with monthly <span><math><msup><mrow><mi>R</mi></mrow><mrow><mn>2</mn></mrow></msup></math></span> of 13.63% and 11.32%, respectively. This predictive power outperforms and complements those of popular economic variables and uncertainty measures. Further analysis shows that a mean–variance investor can obtain considerable economic gains based on the return forecasts of GFU. By dissecting the GFU’s predictability, we observe that the strong forecasting efficacy of GFU for crude oil price returns may stem from its notable power during high-risk conditions and its significant effects on oil demand dynamics.</div></div>","PeriodicalId":14444,"journal":{"name":"International Review of Economics & Finance","volume":"96 ","pages":"Article 103723"},"PeriodicalIF":4.8000,"publicationDate":"2024-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Review of Economics & Finance","FirstCategoryId":"96","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S1059056024007159","RegionNum":2,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"BUSINESS, FINANCE","Score":null,"Total":0}
引用次数: 0
Abstract
In this paper, we introduce an informative uncertainty measure, global financial uncertainty (GFU), for the prediction of crude oil price returns. We find that GFU exhibits significant and remarkable forecasting power for crude oil price returns both in- and out-of-sample with monthly of 13.63% and 11.32%, respectively. This predictive power outperforms and complements those of popular economic variables and uncertainty measures. Further analysis shows that a mean–variance investor can obtain considerable economic gains based on the return forecasts of GFU. By dissecting the GFU’s predictability, we observe that the strong forecasting efficacy of GFU for crude oil price returns may stem from its notable power during high-risk conditions and its significant effects on oil demand dynamics.
期刊介绍:
The International Review of Economics & Finance (IREF) is a scholarly journal devoted to the publication of high quality theoretical and empirical articles in all areas of international economics, macroeconomics and financial economics. Contributions that facilitate the communications between the real and the financial sectors of the economy are of particular interest.