Volatility forecasting for crude oil based on text information and deep learning PSO-LSTM model
Xingrui Jiao, Yuping Song, Yang Kong, Xiaolong Tang
| Year of publication: |
2022
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|---|---|
| Authors: | Jiao, Xingrui ; Song, Yuping ; Kong, Yang ; Tang, Xiaolong |
| Published in: |
Journal of forecasting. - New York, NY : Wiley Interscience, ISSN 1099-131X, ZDB-ID 2001645-1. - Vol. 41.2022, 5, p. 933-944
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| Subject: | crude oil news headlines | LSTM model | market volatility | PSO algorithm | text mining technology | Volatilität | Volatility | Ölmarkt | Oil market | Theorie | Theory | Prognoseverfahren | Forecasting model | ARCH-Modell | ARCH model | Ölpreis | Oil price | Erdöl | Petroleum |
| Type of publication: | Article |
|---|---|
| Type of publication (narrower categories): | Aufsatz in Zeitschrift ; Article in journal |
| Language: | English |
| Other identifiers: | 10.1002/for.2839 [DOI] |
| Source: | ECONIS - Online Catalogue of the ZBW |
Persistent link: https://www.econbiz.de/10013287887