A comparison of machine learning methods for predicting the direction of the US stock market on the basis of volatility indices
Giovanni Campisi, Silvia Muzzioli, Bernard De Baets
| Year of publication: |
2024
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|---|---|
| Authors: | Campisi, Giovanni ; Muzzioli, Silvia ; De Baets, Bernard |
| Published in: |
International journal of forecasting. - Amsterdam [u.a.] : Elsevier Science, ISSN 0169-2070, ZDB-ID 1495951-3. - Vol. 40.2024, 3, p. 869-880
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| Subject: | Forecasting | Machine learning | Market risk | US market | Volatility indices | Volatilität | Volatility | Prognoseverfahren | Forecasting model | Aktienmarkt | Stock market | Künstliche Intelligenz | Artificial intelligence | USA | United States | Wirtschaftsindikator | Economic indicator |
freely available
| Type of publication: | Article |
|---|---|
| Type of publication (narrower categories): | Aufsatz in Zeitschrift ; Article in journal |
| Language: | English |
| Other identifiers: | 10.1016/j.ijforecast.2023.07.002 [DOI] |
| Source: | ECONIS - Online Catalogue of the ZBW |
Persistent link: https://www.econbiz.de/10014547222