Stock market volatility forecasting: Do we need high-frequency data?

Citations

Cited by:

1. Dean Fantazzini, 2024. "Adaptive Conformal Inference for Computing Market Risk Measures: An Analysis with Four Thousand Crypto-Assets," JRFM, MDPI, vol. 17(6), pages 1-44, June.
   • Fantazzini, Dean, 2024. "Adaptive Conformal Inference for computing Market Risk Measures: an Analysis with Four Thousands Crypto-Assets," MPRA Paper 121214, University Library of Munich, Germany.
2. Hasanov, Akram Shavkatovich & Burkhanov, Aktam Usmanovich & Usmonov, Bunyod & Khajimuratov, Nizomjon Shukurullaevich & Khurramova, Madina Mansur qizi, 2024. "The role of sudden variance shifts in predicting volatility in bioenergy crop markets under structural breaks," Energy, Elsevier, vol. 293(C).
3. Yan, Xiang & Bai, Jiancheng & Li, Xiafei & Chen, Zhonglu, 2022. "Can dimensional reduction technology make better use of the information of uncertainty indices when predicting volatility of Chinese crude oil futures?," Resources Policy, Elsevier, vol. 75(C).
4. Haukvik, Nicole & Cheraghali, Hamid & Molnár, Peter, 2024. "The role of investors’ fear in crude oil volatility forecasting," Research in International Business and Finance, Elsevier, vol. 70(PB).
5. Ma, Feng & Wang, Jiqian & Wahab, M.I.M. & Ma, Yuanhui, 2023. "Stock market volatility predictability in a data-rich world: A new insight," International Journal of Forecasting, Elsevier, vol. 39(4), pages 1804-1819.
6. Luo, Jiawen & Cepni, Oguzhan & Demirer, Riza & Gupta, Rangan, 2025. "Forecasting multivariate volatilities with exogenous predictors: An application to industry diversification strategies," Journal of Empirical Finance, Elsevier, vol. 81(C).
   • Jiawen Luo & Oguzhan Cepni & Riza Demirer & Rangan Gupta, 2022. "Forecasting Multivariate Volatilities with Exogenous Predictors: An Application to Industry Diversification Strategies," Working Papers 202258, University of Pretoria, Department of Economics.
7. Li, Zhao-Chen & Xie, Chi & Zeng, Zhi-Jian & Wang, Gang-Jin & Zhang, Ting, 2023. "Forecasting global stock market volatilities in an uncertain world," International Review of Financial Analysis, Elsevier, vol. 85(C).
8. Minh Vo, 2025. "Measuring and Forecasting Stock Market Volatilities with High-Frequency Data," Computational Economics, Springer;Society for Computational Economics, vol. 65(6), pages 3503-3544, June.
9. Bauwens, Luc & Xu, Yongdeng, 2023. "The contribution of realized covariance models to the economic value of volatility timing," Cardiff Economics Working Papers E2023/20, Cardiff University, Cardiff Business School, Economics Section.
   • Bauwens, Luc & Xu, Yongdeng, 2023. "The contribution of realized covariance models to the economic value of volatility timing," LIDAM Discussion Papers CORE 2023018, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
10. Yu, Wei & Zheng, Ying & Jia, Jianjun, 2025. "Political uncertainty and stock performance: Evidence from sessions of the Chinese Provincial People’s Congress," Research in International Business and Finance, Elsevier, vol. 75(C).
11. Horváth, Roman & Kalistová, Anna & Lyócsa, Štefan & Miškufová, Marta & Moravcová, Michala, 2025. "Do hurricanes cause storm on the stock market? The case of US energy companies," International Review of Financial Analysis, Elsevier, vol. 97(C).
12. Xingyu Dai & Roy Cerqueti & Qunwei Wang & Ling Xiao, 2025. "Volatility forecasting: a new GARCH-type model for fuzzy sets-valued time series," Annals of Operations Research, Springer, vol. 348(1), pages 735-775, May.
13. Zhu, Haibin & Bai, Lu & He, Lidan & Liu, Zhi, 2023. "Forecasting realized volatility with machine learning: Panel data perspective," Journal of Empirical Finance, Elsevier, vol. 73(C), pages 251-271.
14. Fantazzini, Dean, 2023. "Assessing the Credit Risk of Crypto-Assets Using Daily Range Volatility Models," MPRA Paper 117141, University Library of Munich, Germany.
15. Sercan Demiralay & Hatice Gaye Gencer & Alexander Brauneis, 2025. "Stock–Commodity Correlations, Optimal Hedging, and Climate Risks," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 45(10), pages 1693-1716, October.
16. He, Mengxi & Wen, Danyan & Xing, Lu & Zhang, Yaojie, 2024. "Industry volatility concentration and the predictability of aggregate stock market volatility," International Review of Economics & Finance, Elsevier, vol. 95(C).
17. Guo, Yangli & Li, Pan & Wu, Hanlin, 2023. "Jumps in the Chinese crude oil futures volatility forecasting: New evidence," Energy Economics, Elsevier, vol. 126(C).
18. Hassanniakalager, Arman & Baker, Paul L. & Platanakis, Emmanouil, 2024. "A False Discovery Rate approach to optimal volatility forecasting model selection," International Journal of Forecasting, Elsevier, vol. 40(3), pages 881-902.
19. Lyu, Yongjian & Yang, Zhidan & Luo, Ya & Qin, Zhilong & Yi, Heling & Ke, Rui, 2025. "Forecasting the volatility of crude oil futures market: Does the simple 5-minute RV hold up?," Energy Economics, Elsevier, vol. 146(C).
20. Mohammad Al-Shboul & Aktham Maghyereh, 2023. "Did real economic uncertainty drive risk connectedness in the oil–stock nexus during the COVID-19 outbreak? A partial wavelet coherence analysis," Journal of Economic Structures, Springer;Pan-Pacific Association of Input-Output Studies (PAPAIOS), vol. 12(1), pages 1-23, December.
21. Guan, Zhigui & Zhao, Yuanjun, 2024. "Optimizing stock market volatility predictions based on the SMVF-ANP approach," International Review of Economics & Finance, Elsevier, vol. 95(C).
22. Wang, Lu & Wang, Xing & Liang, Chao, 2024. "Natural gas volatility prediction via a novel combination of GARCH-MIDAS and one-class SVM," The Quarterly Review of Economics and Finance, Elsevier, vol. 98(C).
23. Werner Kristjanpoller, 2024. "A hybrid econometrics and machine learning based modeling of realized volatility of natural gas," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 10(1), pages 1-32, December.
24. Zhang, Qun & Zhang, Zhendong & Luo, Jiawen, 2024. "Asymmetric and high-order risk transmission across VIX and Chinese futures markets," International Review of Financial Analysis, Elsevier, vol. 93(C).
25. Lan, Qiujun & Li, Haojie & Mi, Xianhua & Zhang, Chunyu, 2025. "Optimizing investment strategies: Harnessing the power of K-line complex networks," International Review of Economics & Finance, Elsevier, vol. 99(C).
26. Fiszeder, Piotr & Fałdziński, Marcin & Molnár, Peter, 2023. "Modeling and forecasting dynamic conditional correlations with opening, high, low, and closing prices," Journal of Empirical Finance, Elsevier, vol. 70(C), pages 308-321.