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Forecasting stock returns: Do less powerful predictors help?. (2019). Shi, Benshan ; Ma, Feng ; Zeng, Qing ; Zhang, Yaojie.
In: Economic Modelling.
RePEc:eee:ecmode:v:78:y:2019:i:c:p:32-39.

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Cited: 22

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  1. Forecasting carbon prices under diversified attention: A dynamic model averaging approach with common factors. (2024). Zhang, Yaojie ; Wang, Qunwei.
    In: Energy Economics.
    RePEc:eee:eneeco:v:133:y:2024:i:c:s0140988324002457.

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  2. Default return spread: A powerful predictor of crude oil price returns. (2023). He, Mengxi ; Han, Qingxiang ; Umar, Muhammad ; Zhang, Yaojie.
    In: Journal of Forecasting.
    RePEc:wly:jforec:v:42:y:2023:i:7:p:1786-1804.

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  3. Machine learning for US cross-industry return predictability under information uncertainty. (2023). Khlifi, Foued ; ben Lahouel, Bechir ; ben Zaied, Younes ; Awijen, Haithem.
    In: Research in International Business and Finance.
    RePEc:eee:riibaf:v:64:y:2023:i:c:s0275531923000193.

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  4. Intraday and overnight tail risks and return predictability in the crude oil market: Evidence from oil-related regular news and extreme shocks. (2023). Bouri, Elie ; Wang, Cheng ; Zhang, Dingsheng ; Xu, Yahua.
    In: Energy Economics.
    RePEc:eee:eneeco:v:127:y:2023:i:pb:s0140988323006199.

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  5. Combination forecasts of Chinas oil futures returns based on multiple uncertainties and their connectedness with oil. (2023). Li, Xiafei ; Wei, YU ; Shi, Chunpei ; Liu, Yuntong.
    In: Energy Economics.
    RePEc:eee:eneeco:v:126:y:2023:i:c:s0140988323005352.

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  6. Forecasting stock return volatility in data-rich environment: A new powerful predictor. (2023). Li, Tingyu ; Zhang, Xiaotong ; Dai, Zhifeng.
    In: The North American Journal of Economics and Finance.
    RePEc:eee:ecofin:v:64:y:2023:i:c:s1062940822001802.

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  8. Which uncertainty is powerful to forecast crude oil market volatility? New evidence. (2022). Wei, YU ; Li, Xiafei ; Chen, Wang ; Liang, Chao ; Ma, Feng.
    In: International Journal of Finance & Economics.
    RePEc:wly:ijfiec:v:27:y:2022:i:4:p:4279-4297.

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  9. Renewable energy stocks forecast using Twitter investor sentiment and deep learning. (2022). Naranpanawa, Athula ; Su, Jen-Je ; Constantino, Michel ; Herrera, Gabriel Paes.
    In: Energy Economics.
    RePEc:eee:eneeco:v:114:y:2022:i:c:s0140988322004170.

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  10. Good variance, bad variance, and stock return predictability. (2021). Zhang, YI ; Liang, Chao ; Ma, Feng.
    In: International Journal of Finance & Economics.
    RePEc:wly:ijfiec:v:26:y:2021:i:3:p:4410-4423.

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  11. On equity market inefficiency during the COVID-19 pandemic. (2021). Vecer, Jan ; Taylor, Stephen ; Navratil, Robert.
    In: International Review of Financial Analysis.
    RePEc:eee:finana:v:77:y:2021:i:c:s105752192100154x.

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  12. The skewness of oil price returns and equity premium predictability. (2021). Wen, Fenghua ; Kang, Jie ; Zhou, Huiting ; Dai, Zhifeng.
    In: Energy Economics.
    RePEc:eee:eneeco:v:94:y:2021:i:c:s0140988320304096.

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  13. Economic policy uncertainty and stock market returns: New evidence. (2021). Liang, Chao ; Chen, Zhonglu ; Wang, Jianqiong ; Xu, Yongan.
    In: The North American Journal of Economics and Finance.
    RePEc:eee:ecofin:v:58:y:2021:i:c:s1062940821001418.

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  14. Indicator selection and stock return predictability. (2021). Zhu, Huan ; Dai, Zhifeng.
    In: The North American Journal of Economics and Finance.
    RePEc:eee:ecofin:v:57:y:2021:i:c:s1062940821000309.

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  15. Intraday momentum and return predictability: Evidence from the crude oil market. (2021). Gong, XU ; Wen, Zhuzhu ; Xu, Yahua ; Ma, Diandian.
    In: Economic Modelling.
    RePEc:eee:ecmode:v:95:y:2021:i:c:p:374-384.

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  16. Forecasting global equity market volatilities. (2020). Liao, Yin ; Ma, Feng ; Zhang, Yaojie.
    In: International Journal of Forecasting.
    RePEc:eee:intfor:v:36:y:2020:i:4:p:1454-1475.

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  17. Global predictive power of the upside and downside variances of the U.S. equity market. (2020). Zhang, Liguo ; Xiao, Jun ; Xu, Yahua.
    In: Economic Modelling.
    RePEc:eee:ecmode:v:93:y:2020:i:c:p:605-619.

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  18. Improving forecasting performance of realized covariance with extensions of HAR-RCOV model: statistical significance and economic value. (2019). Liu, LI ; Wei, YU ; Zhang, Yaojie.
    In: Quantitative Finance.
    RePEc:taf:quantf:v:19:y:2019:i:9:p:1425-1438.

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  19. Economic constraints and stock return predictability: A new approach. (2019). Wei, YU ; Zhang, Yaojie ; Yi, Yongsheng ; Ma, Feng.
    In: International Review of Financial Analysis.
    RePEc:eee:finana:v:63:y:2019:i:c:p:1-9.

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  20. Forecasting oil price volatility: Forecast combination versus shrinkage method. (2019). Wei, YU ; Zhang, Yaojie ; Jin, Daxiang.
    In: Energy Economics.
    RePEc:eee:eneeco:v:80:y:2019:i:c:p:423-433.

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  21. Forecasting crude oil prices with a large set of predictors: Can LASSO select powerful predictors?. (2019). Wang, Yudong ; Ma, Feng ; Zhang, Yaojie.
    In: Journal of Empirical Finance.
    RePEc:eee:empfin:v:54:y:2019:i:c:p:97-117.

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