1. Yuqin Huang, Feng Li, Tong Li and Tse-Chun Lin (2024), “Local Information Advantage and Stock Returns: Evidence from Social Media”, Contemporary Accounting Research. Vol. 41(2), pp. 1089-1119.
2. Li Li, Yanfei Kang and Feng Li* (2023), “Bayesian Forecast Combination Using Time-Varying Features”, International Journal of Forecasting. Vol. 39(3), pp. 1287-1302.
3. Li Li, Yanfei Kang, Fotios Petropoulos and Feng Li* (2023), “Feature-Based Intermittent Demand Forecast Combinations: Accuracy and Inventory Implications”, International Journal of Production Research. Vol. 61(22), pp. 7557-7572.
4. Xiaoqian Wang, Yanfei Kang, Rob J. Hyndman and Feng Li* (2023), “Distributed ARIMA Models for Ultra-Long Time Series”, International Journal of Forecasting. Vol. 39(3), pp. 1163-1184.
5. Bohan Zhang, Yanfei Kang, Anastasios Panagiotelis and Feng Li* (2023), “Optimal Reconciliation with Immutable Forecasts”, European Journal of Operational Research. Vol. 308(1), pp. 650-660.
6. Xiaoqian Wang, Yanfei Kang, Fotios Petropoulos and Feng Li* (2022), “The Uncertainty Estimation of Feature-Based Forecast Combinations”, Journal of the Operational Research Society. Vol. 73(5), pp. 979-993.
7. Yanfei Kang, Wei Cao, Fotios Petropoulos and Feng Li* (2022), “Forecast with Forecasts: Diversity Matters”, European Journal of Operational Research.Vol. 301(1), pp. 180-190.
8. Matthias Anderer and Feng Li* (2022), “Hierarchical Forecasting with a Top-down Alignment of Independent-Level Forecasts”, International Journal of Forecasting. Vol. 38(4), pp. 1405-1414.
9. Xuening Zhu, Feng Li* and Hansheng Wang (2021), “Least-Square Approximation for a Distributed System”, Journal of Computational and Graphical Statistics. Vol. 30(4), pp. 1004-1018.
10. Feng Li and Yanfei Kang (2018), “Improving Forecasting Performance Using Covariate-Dependent Copula Models”, International Journal of Forecasting. Vol. 34(3), pp. 456-476.
