Commodity prices after COVID-19 : persistence and time trends
Year of publication: |
2022
|
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Authors: | Monge González, Manuel ; Lazcano, Ana |
Subject: | commodity prices | COVID-19 | ARFIMA (p, d, q) model | machine learning | Rohstoffpreis | Commodity price | Coronavirus | Welt | World | Künstliche Intelligenz | Artificial intelligence | Wirkungsanalyse | Impact assessment | Rohstoffmarkt | Commodity market | Schock | Shock |
Type of publication: | Article |
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Type of publication (narrower categories): | Aufsatz in Zeitschrift ; Article in journal |
Language: | English |
Other identifiers: | 10.3390/risks10060128 [DOI] |
Classification: | C22 - Time-Series Models ; C45 - Neural Networks and Related Topics ; E30 - Prices, Business Fluctuations, and Cycles. General ; G10 - General Financial Markets. General ; G17 - Financial Forecasting ; q02 |
Source: | ECONIS - Online Catalogue of the ZBW |
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