{"title":"What drives the uranium sector risk? The role of attention, economic and geopolitical uncertainty","authors":"Štefan Lyócsa , Neda Todorova","doi":"10.1016/j.eneco.2024.107980","DOIUrl":null,"url":null,"abstract":"<div><div>Interest in nuclear energy has increased recently due to its low-carbon footprint, energy security concerns, and technological advances. Despite the recent surge in uranium stocks, there is a lack of research on uranium sector volatility. We fill this gap by analyzing the volatility of the Global X Uranium ETF (URA) from 2010 to 2024 using high-frequency data. Our analysis reveals that HAR models effectively capture URA volatility. Market-wide implied volatility and investor attention, captured by Google search volume, are found to contain valuable information for forecasting uranium sector volatility in an in-sample context. In contrast, economic and geopolitical uncertainty, as well as global financial risk, exhibit limited relevance. Although advanced models show some improvement in out-of-sample predictions, the basic HAR model remains a robust benchmark.</div></div>","PeriodicalId":11665,"journal":{"name":"Energy Economics","volume":"140 ","pages":"Article 107980"},"PeriodicalIF":13.6000,"publicationDate":"2024-10-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Energy Economics","FirstCategoryId":"96","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0140988324006881","RegionNum":2,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"ECONOMICS","Score":null,"Total":0}
引用次数: 0
Abstract
Interest in nuclear energy has increased recently due to its low-carbon footprint, energy security concerns, and technological advances. Despite the recent surge in uranium stocks, there is a lack of research on uranium sector volatility. We fill this gap by analyzing the volatility of the Global X Uranium ETF (URA) from 2010 to 2024 using high-frequency data. Our analysis reveals that HAR models effectively capture URA volatility. Market-wide implied volatility and investor attention, captured by Google search volume, are found to contain valuable information for forecasting uranium sector volatility in an in-sample context. In contrast, economic and geopolitical uncertainty, as well as global financial risk, exhibit limited relevance. Although advanced models show some improvement in out-of-sample predictions, the basic HAR model remains a robust benchmark.
最近,由于核能的低碳足迹、能源安全问题和技术进步,人们对核能的兴趣与日俱增。尽管近期铀股大涨,但缺乏对铀行业波动性的研究。我们利用高频数据分析了 Global X Uranium ETF (URA) 从 2010 年到 2024 年的波动性,填补了这一空白。我们的分析表明,HAR 模型能有效捕捉 URA 的波动性。通过谷歌搜索量捕捉到的全市场隐含波动率和投资者关注度被认为包含了在样本环境下预测铀行业波动率的宝贵信息。相比之下,经济和地缘政治不确定性以及全球金融风险的相关性有限。虽然高级模型在样本外预测方面有所改进,但基本 HAR 模型仍然是一个稳健的基准。
期刊介绍:
Energy Economics is a field journal that focuses on energy economics and energy finance. It covers various themes including the exploitation, conversion, and use of energy, markets for energy commodities and derivatives, regulation and taxation, forecasting, environment and climate, international trade, development, and monetary policy. The journal welcomes contributions that utilize diverse methods such as experiments, surveys, econometrics, decomposition, simulation models, equilibrium models, optimization models, and analytical models. It publishes a combination of papers employing different methods to explore a wide range of topics. The journal's replication policy encourages the submission of replication studies, wherein researchers reproduce and extend the key results of original studies while explaining any differences. Energy Economics is indexed and abstracted in several databases including Environmental Abstracts, Fuel and Energy Abstracts, Social Sciences Citation Index, GEOBASE, Social & Behavioral Sciences, Journal of Economic Literature, INSPEC, and more.