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Forecasting crude oil prices with a large set of predictors : Can LASSO select powerful predictors?
Zhang, Yaojie; Ma, Feng; Wang, Yudong - In: Journal of empirical finance 54 (2019), pp. 97-117
Persistent link: https://www.econbiz.de/10012174816
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Predicting the long-term stock market volatility : a GARCH-MIDAS model with variable selection
Fang, Tong; Lee, Tae-hwy; Su, Zhi - In: Journal of empirical finance 58 (2020), pp. 36-49
Persistent link: https://www.econbiz.de/10012430452
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Forecasting tail risk measures for financial time series : an extreme value approach with covariates
James, Robert; Leung, Henry; Leung, Jessica Wai Yin; … - In: Journal of empirical finance 71 (2023), pp. 29-50
Persistent link: https://www.econbiz.de/10014292519
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A toolkit for exploiting contemporaneous stock correlations
Hiraki, Kazuhiro; Sun, Chuanping - In: Journal of empirical finance 65 (2022), pp. 99-124
Persistent link: https://www.econbiz.de/10013286402
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Factor correlation and the cross section of asset returns : a correlation-robust machine learning approach
Sun, Chuanping - In: Journal of empirical finance 77 (2024), pp. 1-16
Persistent link: https://www.econbiz.de/10014578566
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Modelling market implied ratings using LASSO variable selection techniques
Sermpinis, Georgios; Tsoukas, Serafeim; Zhang, Ping - In: Journal of empirical finance 48 (2018), pp. 19-35
Persistent link: https://www.econbiz.de/10012109239
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Forecasting realized betas using predictors indicating structural breaks and asymmetric risk effects
Luo, Jiawen; Chen, Zhenbiao; Cheng, Mingmian - In: Journal of empirical finance 80 (2025), pp. 1-24
Persistent link: https://www.econbiz.de/10015329724