| Geopolitical risk uncertainty and oil future volatility: Evidence from MIDAS models D Mei, F Ma, Y Liao, L Wang Energy Economics 86, 104624, 2020 | 169 | 2020 |
| Forecasting stock price volatility: New evidence from the GARCH-MIDAS model L Wang, F Ma, J Liu, L Yang International Journal of Forecasting 36 (2), 684-694, 2020 | 135 | 2020 |
| Crude oil and BRICS stock markets under extreme shocks: New evidence L Wang, F Ma, T Niu, C He Economic Modelling 86, 54-68, 2020 | 93 | 2020 |
| The information content of uncertainty indices for natural gas futures volatility forecasting C Liang, F Ma, L Wang, Q Zeng Journal of Forecasting, 2021 | 67 | 2021 |
| The importance of extreme shock: Examining the effect of investor sentiment on the crude oil futures market L Wang, F Ma, T Niu, C Liang Energy Economics 99, 105319, 2021 | 51 | 2021 |
| Global economic policy uncertainty and gold futures market volatility: Evidence from Markov‐regime switching GARCH‐MIDAS models F Ma, X Lu, L Wang, J Chevallier Journal of Forecasting, 2021 | 43 | 2021 |
| Impact of financial instability on international crude oil volatility: new sight from a regime-switching framework Y Hong, L Wang, C Liang, M Umar Resources Policy 77, 102667, 2022 | 39 | 2022 |
| Forecasting crude oil volatility with geopolitical risk: Do time-varying switching probabilities play a role? L Wang, F Ma, J Hao, X Gao International Review of Financial Analysis 76, 101756, 2021 | 35 | 2021 |
| Portfolio optimization of financial commodities with energy futures L Wang, F Ahmad, G Luo, M Umar, D Kirikkaleli Annals of Operations Research 313 (1), 401-439, 2022 | 34 | 2022 |
| Extreme risk transmission among bitcoin and crude oil markets D Li, Y Hong, L Wang, P Xu, Z Pan Resources Policy 77, 102761, 2022 | 30 | 2022 |
| Forecasting renewable energy stock volatility using short and long-term Markov switching GARCH-MIDAS models: Either, neither or both? L Wang, J Wu, Y Cao, Y Hong Energy Economics 111, 106056, 2022 | 28 | 2022 |
| Pricing geometric Asian rainbow options under fractional Brownian motion L Wang, R Zhang, L Yang, Y Su, F Ma Physica A: Statistical Mechanics and its Applications 494, 8-16, 2018 | 26 | 2018 |
| Natural gas volatility prediction: Fresh evidence from extreme weather and extended GARCH-MIDAS-ES model C Liang, Z Xia, X Lai, L Wang Energy Economics 116, 106437, 2022 | 24 | 2022 |
| How does the COVID-19 outbreak affect the causality between gold and the stock market? New evidence from the extreme Granger causality test Y Hong, F Ma, L Wang, C Liang Resources Policy 78, 102859, 2022 | 22 | 2022 |
| Dynamic asymmetric impact of equity market uncertainty on energy markets: A time-varying causality analysis Y Hong, L Wang, X Ye, Y Zhang Renewable Energy 196, 535-546, 2022 | 22 | 2022 |
| Forecasting stock volatility in the presence of extreme shocks: Short‐term and long‐term effects L Wang, F Ma, G Liu Journal of Forecasting 39 (5), 797-810, 2020 | 22 | 2020 |
| Research on green innovation of the great Changsha-Zhuzhou-Xiangtan city group based on network L Wang, W Ye, L Chen Land 10 (11), 1198, 2021 | 17 | 2021 |
| Do extreme shocks help forecast oil price volatility? The augmented GARCH‐MIDAS approach L Wang, F Ma, G Liu, Q Lang International Journal of Finance & Economics, 2021 | 17 | 2021 |
| Predicting the volatility of China's new energy stock market: Deep insight from the realized EGARCH-MIDAS model L Wang, C Zhao, C Liang, S Jiu Finance Research Letters 48, 102981, 2022 | 12 | 2022 |
| How macro-variables drive crude oil volatility? Perspective from the STL-based iterated combination method L Zhang, L Wang, X Wang, Y Zhang, Z Pan Resources Policy 77, 102656, 2022 | 11 | 2022 |
Feng MaSchool of Economics & Management, Southwest Jiaotong UniversityVerified email at swjtu.edu.cn
