Forecasting the aggregate stock market volatility in a data-rich world

Citations

Cited by:

1. Dai, Zhifeng & Zhang, Xiaotong & Li, Tingyu, 2023. "Forecasting stock return volatility in data-rich environment: A new powerful predictor," The North American Journal of Economics and Finance, Elsevier, vol. 64(C).
2. Li, Xiaodan & Gong, Xue & Xing, Lu, 2024. "The impact of presidential economic approval rating on stock volatility: An industrial perspective," Finance Research Letters, Elsevier, vol. 63(C).
3. Song, Ziyu & Gong, Xiaomin & Zhang, Cheng & Yu, Changrui, 2023. "Investor sentiment based on scaled PCA method: A powerful predictor of realized volatility in the Chinese stock market," International Review of Economics & Finance, Elsevier, vol. 83(C), pages 528-545.
4. Chen, Juan & Ma, Feng & Qiu, Xuemei & Li, Tao, 2023. "The role of categorical EPU indices in predicting stock-market returns," International Review of Economics & Finance, Elsevier, vol. 87(C), pages 365-378.
5. Hyder Ali & Salma Naz, 2025. "Forecasting Equity Premium in the Face of Climate Policy Uncertainty," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 44(2), pages 513-546, March.
6. Zhikai Zhang & Yaojie Zhang & Yudong Wang & Qunwei Wang, 2024. "The predictability of carbon futures volatility: New evidence from the spillovers of fossil energy futures returns," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 44(4), pages 557-584, April.
7. Guo, Yangli & Ma, Feng & Li, Haibo & Lai, Xiaodong, 2022. "Oil price volatility predictability based on global economic conditions," International Review of Financial Analysis, Elsevier, vol. 82(C).
8. He, Mengxi & Wang, Yudong & Zeng, Qing & Zhang, Yaojie, 2023. "Forecasting aggregate stock market volatility with industry volatilities: The role of spillover index," Research in International Business and Finance, Elsevier, vol. 65(C).
9. Yuan, Xianghui & Li, Xiang, 2022. "Delta-hedging demand and intraday momentum: Evidence from China," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 600(C).
10. Yu, Xing & Li, Yanyan & Gong, Xue & Zhang, Nan, 2022. "Evaluating the performance of futures hedging using factors-driven realized volatility," International Review of Financial Analysis, Elsevier, vol. 84(C).
11. Zhang, Zhikai & He, Mengxi & Zhang, Yaojie & Wang, Yudong, 2021. "Realized skewness and the short-term predictability for aggregate stock market volatility," Economic Modelling, Elsevier, vol. 103(C).
12. Pavan Kumar Nagula & Christos Alexakis, 2022. "A Novel Machine Learning Approach for Predicting the NIFTY50 Index in India," International Advances in Economic Research, Springer;International Atlantic Economic Society, vol. 28(3), pages 155-170, November.
13. Gong, Xue & Zhang, Weiguo & Wang, Junbo & Wang, Chao, 2022. "Investor sentiment and stock volatility: New evidence," International Review of Financial Analysis, Elsevier, vol. 80(C).
14. Ghani, Maria & Guo, Qiang & Ma, Feng & Li, Tao, 2022. "Forecasting Pakistan stock market volatility: Evidence from economic variables and the uncertainty index," International Review of Economics & Finance, Elsevier, vol. 80(C), pages 1180-1189.
15. Juan D. Díaz & Erwin Hansen & Gabriel Cabrera, 2025. "Forecasting the Volatility of US Oil and Gas Firms With Machine Learning," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 44(4), pages 1383-1402, July.
16. Li, Zhao-Chen & Xie, Chi & Wang, Gang-Jin & Zhu, You & Zeng, Zhi-Jian & Gong, Jue, 2024. "Forecasting global stock market volatilities: A shrinkage heterogeneous autoregressive (HAR) model with a large cross-market predictor set," International Review of Economics & Finance, Elsevier, vol. 93(PB), pages 673-711.
17. Ma, Feng & Guo, Yangli & Chevallier, Julien & Huang, Dengshi, 2022. "Macroeconomic attention, economic policy uncertainty, and stock volatility predictability," International Review of Financial Analysis, Elsevier, vol. 84(C).
18. Shi, Qi, 2025. "Technical indicators and aggregate stock returns: An updated look," Journal of Multinational Financial Management, Elsevier, vol. 77(C).
19. Mei, Dexiang & Li, Xiaotao, 2026. "Forecasting of Chinese stock price using a hybrid neural network model," Research in International Business and Finance, Elsevier, vol. 82(C).
20. Li, Xiaodan & Gong, Xue & Ge, Futing & Huang, Jingjing, 2024. "Forecasting stock volatility using pseudo-out-of-sample information," International Review of Economics & Finance, Elsevier, vol. 90(C), pages 123-135.
21. Guo, Yangli & He, Feng & Liang, Chao & Ma, Feng, 2022. "Oil price volatility predictability: New evidence from a scaled PCA approach," Energy Economics, Elsevier, vol. 105(C).
22. Muhammad Kamran Khan & Jian‐Zhou Teng & Muhammad Imran Khan & Muhammad Fayaz Khan, 2023. "Stock market reaction to macroeconomic variables: An assessment with dynamic autoregressive distributed lag simulations," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 28(3), pages 2436-2448, July.
23. Xiafei Li & Chao Liang & Feng Ma, 2025. "Forecasting stock market volatility with a large number of predictors: New evidence from the MS-MIDAS-LASSO model," Annals of Operations Research, Springer, vol. 352(3), pages 613-652, September.
24. Zhou, Zhiping & Wang, Kai, 2025. "War discourse predicts stock market volatility: A century of evidence," Finance Research Letters, Elsevier, vol. 82(C).
25. Danyan Wen & Mengxi He & Yaojie Zhang & Yudong Wang, 2022. "Forecasting realized volatility of Chinese stock market: A simple but efficient truncated approach," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 41(2), pages 230-251, March.
26. Wang, Zhenxin & Wang, Shaoping & Yan, Yayi & Xia, Yingcun, 2025. "Examining Chinese volume–volatility nexus: A regime-switching perspective," Economic Modelling, Elsevier, vol. 144(C).