What drives the uranium sector risk? The role of attention, economic and geopolitical uncertainty

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. • First study to analyze uranium sector volatility. • High-frequency data based in- and out-of-sample analysis of Global X Uranium ETF. • VIX and Google search volume relevant in-sample for uranium sector risk (URA). • Geopolitical and financial risk proxies of limited relevance.

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Publication Details

Journal
Energy Economics
Published
2024-10-28
DOI
https://doi.org/10.1016/j.eneco.2024.107980
Citations
12
Primary Topic
Market Dynamics and Volatility
Type
article
Field-Weighted Citation Impact
13.55
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article

What drives the uranium sector risk? The role of attention, economic and geopolitical uncertainty

Neda Todorova, Štefan Lyócsa
12 citations
Energy Economics
Market Dynamics and Volatility
13.55
article

What drives the uranium sector risk? The role of attention, economic and geopolitical uncertainty

Neda Todorova, Štefan Lyócsa
article en
12 citations

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. • First study to analyze uranium sector volatility. • High-frequency data based in- and out-of-sample analysis of Global X Uranium ETF. • VIX and Google search volume relevant in-sample for uranium sector risk (URA). • Geopolitical and financial risk proxies of limited relevance.

Energy EconomicsVol. 140
Griffith University (AU), University of Prešov (SK), Slovak Academy of Sciences (SK), Masaryk University (CZ), Institute of Economic Research of the Slovak Academy of Sciences (SK)
Openalex Percentile: Top 2%
Market Dynamics and Volatility
13.55
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