A novel hybrid approach to forecast crude oil futures using intraday data
Jeevananthan Manickavasagam, S. Visalakshmi, Nicholas Apergis
| Year of publication: |
2020
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|---|---|
| Authors: | Manickavasagam, Jeevananthan ; Visalakshmi, S. ; Apergēs, Nikolaos |
| Published in: |
Technological forecasting & social change : an international journal. - Amsterdam : Elsevier, ISSN 0040-1625, ZDB-ID 280700-2. - Vol. 158.2020, p. 1-11
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| Subject: | Crude oil prices | Forecasting | Flower Pollination model | Machine learning model | Particle Swarm Optimization model | Intraday data | Prognoseverfahren | Forecasting model | Ölpreis | Oil price | Künstliche Intelligenz | Artificial intelligence | ARCH-Modell | ARCH model | Ölmarkt | Oil market | Prognose | Forecast | Erdöl | Petroleum | Rohstoffderivat | Commodity derivative | Volatilität | Volatility | Mathematische Optimierung | Mathematical programming |
| Type of publication: | Article |
|---|---|
| Type of publication (narrower categories): | Aufsatz in Zeitschrift ; Article in journal |
| Language: | English |
| Source: | ECONIS - Online Catalogue of the ZBW |
Persistent link: https://www.econbiz.de/10012516847