Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/311031 
Year of Publication: 
2023
Citation: 
[Journal:] Computational Economics [ISSN:] 1572-9974 [Volume:] 64 [Issue:] 1 [Publisher:] Springer US [Place:] New York, NY [Year:] 2023 [Pages:] 487-513
Publisher: 
Springer US, New York, NY
Abstract: 
We use monthly data covering a century-long sample period (1915–2021) to study whether geopolitical risk helps to forecast subsequent gold volatility. We account not only for geopolitical threats and acts, but also for 39 country-specific sources of geopolitical risk. The response of subsequent volatility is heterogeneous across countries and nonlinear. We find that accounting for geopolitical risk at the country level improves forecast accuracy, especially when we use random forests to estimate our forecasting models. As an extension, we report empirical evidence on the predictive value of the country-level sources of geopolitical risk for two other candidate safe-haven assets, oil and silver, over the sample periods 1900–2021 and 1915–2021, respectively. Our results have important implications for the portfolio and risk-management decisions of investors who seek a safe haven in times of heightened geopolitical tensions.
Subjects: 
Gold
Geopolitical risk
Forecasting
Returns
Volatility
Random forests
JEL: 
C22
D80
H56
Q02
Persistent Identifier of the first edition: 
Creative Commons License: 
cc-by Logo
Document Type: 
Article
Document Version: 
Published Version

Files in This Item:
File
Size





Items in EconStor are protected by copyright, with all rights reserved, unless otherwise indicated.