Forecasting the term structure of commodities future prices using machine learning
Year of publication: |
2023
|
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Authors: | Figueiredo, Mario ; Saporito, Yuri F. |
Published in: |
Digital finance : smart data analytics, investment innovation, and financial technology. - [Cham] : Springer Nature Switzerland AG, ISSN 2524-6186, ZDB-ID 2947479-6. - Vol. 5.2023, 1, p. 57-90
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Subject: | Commodities | Deep learning | Dynamic Nelson-Siegel | Forecasting | Future prices | Schwartz-Smith model | Prognoseverfahren | Forecasting model | Rohstoffderivat | Commodity derivative | Zinsstruktur | Yield curve | Theorie | Theory | Prognose | Forecast | Künstliche Intelligenz | Artificial intelligence | Rohstoffpreis | Commodity price |
Type of publication: | Article |
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Type of publication (narrower categories): | Aufsatz in Zeitschrift ; Article in journal |
Language: | English |
Other identifiers: | 10.1007/s42521-022-00069-3 [DOI] |
Classification: | C14 - Semiparametric and Nonparametric Methods ; G13 - Contingent Pricing; Futures Pricing ; G17 - Financial Forecasting |
Source: | ECONIS - Online Catalogue of the ZBW |
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