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Forecasting oil futures realized range-based volatility with jumps, leverage effect, and regime switching : new evidence from MIDAS models
Lu, Xinjie; Ma, Feng; Wang, Jiqian; Liu, Jing - In: Journal of forecasting 41 (2022) 4, pp. 853-868
Persistent link: https://www.econbiz.de/10013287870
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Volatility forecasting for crude oil based on text information and deep learning PSO-LSTM model
Jiao, Xingrui; Song, Yuping; Kong, Yang; Tang, Xiaolong - In: Journal of forecasting 41 (2022) 5, pp. 933-944
Persistent link: https://www.econbiz.de/10013287887
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Volatility forecasting for stock market index based on complex network and hybrid deep learning model
Song, Yuping; Lei, Bolin; Tang, Xiaolong; Li, Chen - In: Journal of forecasting 43 (2024) 3, pp. 544-566
Persistent link: https://www.econbiz.de/10014532346
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Forecasting international equity market volatility : a new approach
Liang, Chao; Li, Yan; Ma, Feng; Zhang, Yaojie - In: Journal of forecasting 41 (2022) 7, pp. 1433-1457
Persistent link: https://www.econbiz.de/10013465704
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Volatility forecasting for stock market incorporating macroeconomic variables based on GARCH-MIDAS and deep learning models
Song, Yuping; Tang, Xiaolong; Wang, Hemin; Ma, Zhiren - In: Journal of forecasting 42 (2023) 1, pp. 51-59
Persistent link: https://www.econbiz.de/10013465760
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A tug of war of forecasting the US stock market volatility : oil futures overnight versus intraday information
Ma, Feng; Wahab, M. I. M.; Chevallier, Julien; Li, Ziyang - In: Journal of forecasting 42 (2023) 1, pp. 60-75
Persistent link: https://www.econbiz.de/10013465762
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Which factors drive Bitcoin volatility : macroeconomic, technical, or both?
Wang, Jiqian; Ma, Feng; Bouri, Elie; Guo, Yangli - In: Journal of forecasting 42 (2023) 4, pp. 970-988
Persistent link: https://www.econbiz.de/10014292892