Forecasting crude oil volatility using the deep learning-based hybrid models with common factors
Year of publication: |
2024
|
---|---|
Authors: | Yang, Ke ; Hu, Nan ; Tian, Fengping |
Published in: |
The journal of futures markets. - New York, NY : Wiley Interscience, ISSN 1096-9934, ZDB-ID 2002201-3. - Vol. 44.2024, 8, p. 1429-1446
|
Subject: | crude oil future | deep learning | factor structure | volatility forecasting | Volatilität | Volatility | Prognoseverfahren | Forecasting model | Erdöl | Petroleum | Ölpreis | Oil price | Ölmarkt | Oil market | ARCH-Modell | ARCH model | Rohstoffderivat | Commodity derivative | Welt | World |
-
Southern oscillation : great value of its trends for forecasting crude oil spot price volatility
Hong, Yanran, (2023)
-
Zhang, Yue-Jun, (2023)
-
Forecasting the volatility of crude oil futures using intraday data
Sévi, Benoît, (2014)
- More ...
-
A Quantile Regression Approach to Panel Data Analysis of Health Care Expenditure in OECD Countries
Tian, Fengping, (2016)
-
Realized volatility forecast of stock index under structural breaks
Yang, Ke, (2015)
-
Yang, Ke, (2017)
- More ...