IDEAS home Printed from https://ideas.repec.org/a/eee/finlet/v58y2023ipcs1544612323009406.html
   My bibliography  Save this article

Forecasting Sector-Level Stock Market Volatility: The Role of World Uncertainty Index

Author

Listed:
  • Yu, Miao

Abstract

This study investigates the predictive ability of the World Uncertainty Index (WUI) on forecasting sector-level stock market volatility in the Shanghai Stock Exchange. The out-of-sample results demonstrate that the WUI improves volatility predictions, particularly in the materials, industrials, and health care sectors. Further analysis reveals the WUI's stronger predictive capability in high volatility states. The findings highlight the value of the WUI as a tool for anticipating and managing risk in specific sectors of the stock market.

Suggested Citation

  • Yu, Miao, 2023. "Forecasting Sector-Level Stock Market Volatility: The Role of World Uncertainty Index," Finance Research Letters, Elsevier, vol. 58(PC).
  • Handle: RePEc:eee:finlet:v:58:y:2023:i:pc:s1544612323009406
    DOI: 10.1016/j.frl.2023.104568
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S1544612323009406
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.frl.2023.104568?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. N. Bloom, 2016. "Fluctuations in uncertainty," Voprosy Ekonomiki, NP Voprosy Ekonomiki, issue 4.
    2. Ivo Welch & Amit Goyal, 2008. "A Comprehensive Look at The Empirical Performance of Equity Premium Prediction," The Review of Financial Studies, Society for Financial Studies, vol. 21(4), pages 1455-1508, July.
    3. George Bittlingmayer, 1998. "Output, Stock Volatility, and Political Uncertainty in a Natural Experiment: Germany, 1880-1940," Journal of Finance, American Finance Association, vol. 53(6), pages 2243-2257, December.
    4. Charlotte Christiansen & Maik Schmeling & Andreas Schrimpf, 2012. "A comprehensive look at financial volatility prediction by economic variables," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 27(6), pages 956-977, September.
    5. Amengual, Dante & Xiu, Dacheng, 2018. "Resolution of policy uncertainty and sudden declines in volatility," Journal of Econometrics, Elsevier, vol. 203(2), pages 297-315.
    6. Chau, Frankie & Deesomsak, Rataporn & Wang, Jun, 2014. "Political uncertainty and stock market volatility in the Middle East and North African (MENA) countries," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 28(C), pages 1-19.
    7. Clark, Todd E. & West, Kenneth D., 2007. "Approximately normal tests for equal predictive accuracy in nested models," Journal of Econometrics, Elsevier, vol. 138(1), pages 291-311, May.
    8. 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).
    9. John Y. Campbell & Samuel B. Thompson, 2008. "Predicting Excess Stock Returns Out of Sample: Can Anything Beat the Historical Average?," The Review of Financial Studies, Society for Financial Studies, vol. 21(4), pages 1509-1531, July.
    10. Chowdhury, Mohammad Ashraful Ferdous & Meo, Muhammad Saeed & Aloui, Chaker, 2021. "How world uncertainties and global pandemics destabilized food, energy and stock markets? Fresh evidence from quantile on quantile regressions," International Review of Financial Analysis, Elsevier, vol. 76(C).
    11. Feng Ma & Yangli Guo & Julien Chevallier & Dengshi Huang, 2022. "Macroeconomic attention, economic policy uncertainty, and stock volatility predictability," Post-Print halshs-04250304, HAL.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Li, Dakai, 2024. "Forecasting stock market realized volatility: The role of investor attention to the price of petroleum products," International Review of Economics & Finance, Elsevier, vol. 90(C), pages 115-122.
    2. 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).
    3. Liu, Guangqiang & Guo, Xiaozhu, 2022. "Forecasting stock market volatility using commodity futures volatility information," Resources Policy, Elsevier, vol. 75(C).
    4. Nima Nonejad, 2021. "Bayesian model averaging and the conditional volatility process: an application to predicting aggregate equity returns by conditioning on economic variables," Quantitative Finance, Taylor & Francis Journals, vol. 21(8), pages 1387-1411, August.
    5. Luo, Qin & Bu, Jinfeng & Xu, Weiju & Huang, Dengshi, 2023. "Stock market volatility prediction: Evidence from a new bagging model," International Review of Economics & Finance, Elsevier, vol. 87(C), pages 445-456.
    6. Baetje, Fabian & Menkhoff, Lukas, 2016. "Equity premium prediction: Are economic and technical indicators unstable?," International Journal of Forecasting, Elsevier, vol. 32(4), pages 1193-1207.
    7. Gao, Jun & Gao, Xiang & Gu, Chen, 2023. "Forecasting European stock volatility: The role of the UK," International Review of Financial Analysis, Elsevier, vol. 89(C).
    8. Zhang, Yaojie & Lei, Likun & Wei, Yu, 2020. "Forecasting the Chinese stock market volatility with international market volatilities: The role of regime switching," The North American Journal of Economics and Finance, Elsevier, vol. 52(C).
    9. Dai, Zhifeng & Zhu, Huan, 2020. "Stock return predictability from a mixed model perspective," Pacific-Basin Finance Journal, Elsevier, vol. 60(C).
    10. Zhang, Yaojie & Wahab, M.I.M. & Wang, Yudong, 2023. "Forecasting crude oil market volatility using variable selection and common factor," International Journal of Forecasting, Elsevier, vol. 39(1), pages 486-502.
    11. 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).
    12. Dai, Zhifeng & Chang, Xiaoming, 2021. "Forecasting stock market volatility: Can the risk aversion measure exert an important role?," The North American Journal of Economics and Finance, Elsevier, vol. 58(C).
    13. Wang, Yudong & Liu, Li & Ma, Feng & Diao, Xundi, 2018. "Momentum of return predictability," Journal of Empirical Finance, Elsevier, vol. 45(C), pages 141-156.
    14. Gong, Xue & Ye, Xin & Zhang, Weiguo & Zhang, Yue, 2023. "Predicting energy futures high-frequency volatility using technical indicators: The role of interaction," Energy Economics, Elsevier, vol. 119(C).
    15. 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).
    16. Mengxi He & Xianfeng Hao & Yaojie Zhang & Fanyi Meng, 2021. "Forecasting stock return volatility using a robust regression model," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 40(8), pages 1463-1478, December.
    17. Díaz, Juan D. & Hansen, Erwin & Cabrera, Gabriel, 2023. "Gold risk premium estimation with machine learning methods," Journal of Commodity Markets, Elsevier, vol. 31(C).
    18. Chen, Jian & Jiang, Fuwei & Li, Hongyi & Xu, Weidong, 2016. "Chinese stock market volatility and the role of U.S. economic variables," Pacific-Basin Finance Journal, Elsevier, vol. 39(C), pages 70-83.
    19. Andrea Bucci & Giulio Palomba & Eduardo Rossi, 2019. "Does macroeconomics help in predicting stock markets volatility comovements? A nonlinear approach," Working Papers 440, Universita' Politecnica delle Marche (I), Dipartimento di Scienze Economiche e Sociali.
    20. Song, Yixuan & He, Mengxi & Wang, Yudong & Zhang, Yaojie, 2022. "Forecasting crude oil market volatility: A newspaper-based predictor regarding petroleum market volatility," Resources Policy, Elsevier, vol. 79(C).

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:finlet:v:58:y:2023:i:pc:s1544612323009406. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/frl .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.