Unraveling the crystal ball : machine learning models for crude oil and natural gas volatility forecasting
Year of publication: |
2024
|
---|---|
Authors: | Tiwari, Aviral Kumar ; Sharma, Gagan Deep ; Rao, Amar ; Hossain, Mohammad Razib ; Dev, Dhairya |
Published in: |
Energy economics. - Amsterdam [u.a.] : Elsevier Science, ISSN 1873-6181, ZDB-ID 2000893-4. - Vol. 134.2024, Art.-No. 107608, p. 1-28
|
Subject: | Crude oil | Economic policy | Machine learning | Natural gas | RMSE | Volatility forecasting | Volatilität | Volatility | Künstliche Intelligenz | Artificial intelligence | Prognoseverfahren | Forecasting model | Welt | World | Erdgas | ARCH-Modell | ARCH model | Gaswirtschaft | Gas industry | Ölpreis | Oil price | Prognose | Forecast | Erdöl | Petroleum | Ölmarkt | Oil market |
-
Forecasting the volatility of crude oil futures using intraday data
Sévi, Benoît, (2014)
-
Forecasting crude oil volatility with exogenous predictors : as good as it GETS?
Bonnier, Jean-Baptiste, (2022)
-
Feng, Lingbing, (2024)
- More ...
-
Past, present, and future of block-chain in finance
Sharma, Gagan Deep, (2024)
-
Hai Hong Trinh, (2022)
-
Hossain, Mohammad Razib, (2024)
- More ...