Climate risks and predictability of the trading volume of gold : evidence from an INGARCH model
| dc.contributor.author | Karmakar, Sayar | |
| dc.contributor.author | Gupta, Rangan | |
| dc.contributor.author | Cepni, Oguzhan | |
| dc.contributor.author | Rognone, Lavinia | |
| dc.contributor.email | rangan.gupta@up.ac.za | en_US |
| dc.date.accessioned | 2023-07-25T08:06:09Z | |
| dc.date.available | 2023-07-25T08:06:09Z | |
| dc.date.issued | 2023-05 | |
| dc.description | DATA AVAILABILITY : Data is available from Bloomberg with access. | en_US |
| dc.description.abstract | We investigate whether text-based physical or transition climate risks forecast the daily volume of gold trade contracts. Given the count-valued nature of gold volume data, we employ a log-linear Poisson integer-valued generalized autoregressive conditional heteroskedasticity (IN-GARCH) model with a climate-related covariate. We detect that physical risks have a significant predictive power for gold volume at 5- and 22-day-ahead horizons. Additionally, from a full-sample analysis, it emerges that physical risks positively relate with gold volume. Combining these findings, we conclude that gold hedges physical risks at 1-week and 1-month horizons. Similar results hold for platinum and palladium, but not for silver. | en_US |
| dc.description.department | Economics | en_US |
| dc.description.librarian | hj2023 | en_US |
| dc.description.uri | http://www.elsevier.com/locate/resourpol | en_US |
| dc.identifier.citation | Karmakar, S., Gupta, R., Cepni, O. et al. 2023, 'Climate risks and predictability of the trading volume of gold : evidence from an INGARCH model', Resources Policy, vol. 82, art. 103438, pp. 1-8, doi : 10.1016/j.resourpol.2023.103438. | en_US |
| dc.identifier.issn | 0301-4207 (print) | |
| dc.identifier.issn | 1873-7641 (online) | |
| dc.identifier.other | 10.1016/j.resourpol.2023.103438 | |
| dc.identifier.uri | http://hdl.handle.net/2263/91610 | |
| dc.language.iso | en | en_US |
| dc.publisher | Elsevier | en_US |
| dc.rights | © 2023 Elsevier Ltd. All rights reserved. Notice : this is the author’s version of a work that was submitted for publication in Resources Policy. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms are not reflected in this document. A definitive version was subsequently published in Resources Policy, vol. 82, art. 103438, pp. 1-8, 2023. doi : 10.1016/j.resourpol.2023.103438. | en_US |
| dc.subject | Climate risks | en_US |
| dc.subject | Precious metals | en_US |
| dc.subject | Forecasting | en_US |
| dc.subject | Trading volumes | en_US |
| dc.subject | Count data | en_US |
| dc.subject | Integer-valued generalized autoregressive conditional heteroskedasticity (IN-GARCH) | en_US |
| dc.subject | SDG-13: Climate action | en_US |
| dc.subject | SDG-08: Decent work and economic growth | en_US |
| dc.title | Climate risks and predictability of the trading volume of gold : evidence from an INGARCH model | en_US |
| dc.type | Preprint Article | en_US |