IDEAS home Printed from https://ideas.repec.org/a/taf/hbhfxx/v23y2022i3p327-337.html
   My bibliography  Save this article

Investors’ Uncertainty and Forecasting Stock Market Volatility

Author

Listed:
  • Ruipeng Liu
  • Rangan Gupta

Abstract

This article examines whether incorporating investors’ uncertainty, as captured by the conditional volatility of sentiment, can help forecasting volatility of stock markets. In this regard, using the Markov-switching multifractal (MSM) model, we find that investors’ uncertainty can substantially increase the accuracy of the forecasts of stock market volatility according to the forecast encompassing test. We further provide evidence that the MSM outperforms the dynamic conditional correlation-generalized autoregressive conditional heteroskedasticity (DCC-GARCH) model.

Suggested Citation

  • Ruipeng Liu & Rangan Gupta, 2022. "Investors’ Uncertainty and Forecasting Stock Market Volatility," Journal of Behavioral Finance, Taylor & Francis Journals, vol. 23(3), pages 327-337, July.
    • Handle: RePEc:taf:hbhfxx:v:23:y:2022:i:3:p:327-337
    DOI: 10.1080/15427560.2020.1867551
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1080/15427560.2020.1867551
    Download Restriction: Access to full text is restricted to subscribers.
    File URL: https://libkey.io/10.1080/15427560.2020.1867551?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 look for a different version below or search for a different version of it.

    Other versions of this item:

    References listed on IDEAS

    as
    1. Lux, Thomas, 2008. "The Markov-Switching Multifractal Model of Asset Returns: GMM Estimation and Linear Forecasting of Volatility," Journal of Business & Economic Statistics, American Statistical Association, vol. 26, pages 194-210, April.
    2. Gupta, Rangan & Subramaniam, Sowmya & Bouri, Elie & Ji, Qiang, 2021. "Infectious disease-related uncertainty and the safe-haven characteristic of US treasury securities," International Review of Economics & Finance, Elsevier, vol. 71(C), pages 289-298.
    3. Nasr, Adnen Ben & Lux, Thomas & Ajmi, Ahdi Noomen & Gupta, Rangan, 2016. "Forecasting the volatility of the Dow Jones Islamic Stock Market Index: Long memory vs. regime switching," International Review of Economics & Finance, Elsevier, vol. 45(C), pages 559-571.
    4. Rangan Gupta & Chi Keung Marco Lau & Mark E. Wohar, 2019. "The impact of US uncertainty on the Euro area in good and bad times: evidence from a quantile structural vector autoregressive model," Empirica, Springer;Austrian Institute for Economic Research;Austrian Economic Association, vol. 46(2), pages 353-368, May.
    5. Shleifer, Andrei & Summers, Lawrence H, 1990. "The Noise Trader Approach to Finance," Journal of Economic Perspectives, American Economic Association, vol. 4(2), pages 19-33, Spring.
    6. Rangan Gupta & Chi Keung Marco Lau & Stephen M. Miller & Mark E. Wohar, 2019. "US Fiscal Policy and Asset Prices: The Role of Partisan Conflict," International Review of Finance, International Review of Finance Ltd., vol. 19(4), pages 851-862, December.
    7. John Y. Campbell, 2008. "Viewpoint: Estimating the equity premium," Canadian Journal of Economics/Revue canadienne d'économique, John Wiley & Sons, vol. 41(1), pages 1-21, February.
    8. Chuliá, Helena & Guillén, Montserrat & Uribe, Jorge M., 2017. "Measuring uncertainty in the stock market," International Review of Economics & Finance, Elsevier, vol. 48(C), pages 18-33.
    9. Lee, Charles M C & Shleifer, Andrei & Thaler, Richard H, 1991. "Investor Sentiment and the Closed-End Fund Puzzle," Journal of Finance, American Finance Association, vol. 46(1), pages 75-109, March.
    10. repec:bla:jfinan:v:53:y:1998:i:6:p:1839-1885 is not listed on IDEAS
    11. Laurent E. Calvet, 2004. "How to Forecast Long-Run Volatility: Regime Switching and the Estimation of Multifractal Processes," Journal of Financial Econometrics, Oxford University Press, vol. 2(1), pages 49-83.
    12. Harvey, David I & Leybourne, Stephen J & Newbold, Paul, 1998. "Tests for Forecast Encompassing," Journal of Business & Economic Statistics, American Statistical Association, vol. 16(2), pages 254-259, April.
    13. Yu Li & Feng Ma & Yaojie Zhang & Zuoping Xiao, 2019. "Economic policy uncertainty and the Chinese stock market volatility: new evidence," Applied Economics, Taylor & Francis Journals, vol. 51(49), pages 5398-5410, October.
    14. Rangan Gupta & Hardik A. Marfatia & Eric Olson, 2020. "Effect of uncertainty on U.S. stock returns and volatility: evidence from over eighty years of high-frequency data," Applied Economics Letters, Taylor & Francis Journals, vol. 27(16), pages 1305-1311, September.
    15. Rangan Gupta & Godwin Olasehinde-Williams & Mark E. Wohar, 2020. "The impact of US uncertainty shocks on a panel of advanced and emerging market economies," The Journal of International Trade & Economic Development, Taylor & Francis Journals, vol. 29(6), pages 711-721, August.
    16. Calvet, Laurent E. & Fisher, Adlai J. & Thompson, Samuel B., 2006. "Volatility comovement: a multifrequency approach," Journal of Econometrics, Elsevier, vol. 131(1-2), pages 179-215.
    17. Clark, Peter K, 1973. "A Subordinated Stochastic Process Model with Finite Variance for Speculative Prices," Econometrica, Econometric Society, vol. 41(1), pages 135-155, January.
    18. Lamoureux, Christopher G & Lastrapes, William D, 1990. "Persistence in Variance, Structural Change, and the GARCH Model," Journal of Business & Economic Statistics, American Statistical Association, vol. 8(2), pages 225-234, April.
    19. Fang, Libing & Qian, Yichuo & Chen, Ying & Yu, Honghai, 2018. "How does stock market volatility react to NVIX? Evidence from developed countries," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 505(C), pages 490-499.
    20. Liu, Li & Zhang, Tao, 2015. "Economic policy uncertainty and stock market volatility," Finance Research Letters, Elsevier, vol. 15(C), pages 99-105.
    21. Copeland, Thomas E, 1976. "A Model of Asset Trading under the Assumption of Sequential Information Arrival," Journal of Finance, American Finance Association, vol. 31(4), pages 1149-1168, September.
    22. Engle, Robert F, 1982. "Autoregressive Conditional Heteroscedasticity with Estimates of the Variance of United Kingdom Inflation," Econometrica, Econometric Society, vol. 50(4), pages 987-1007, July.
    23. Su, Zhi & Fang, Tong & Yin, Libo, 2019. "Understanding stock market volatility: What is the role of U.S. uncertainty?," The North American Journal of Economics and Finance, Elsevier, vol. 48(C), pages 582-590.
    24. X. Frank Zhang, 2006. "Information Uncertainty and Stock Returns," Journal of Finance, American Finance Association, vol. 61(1), pages 105-137, February.
    25. Chuliá, Helena & Gupta, Rangan & Uribe, Jorge M. & Wohar, Mark E., 2017. "Impact of US uncertainties on emerging and mature markets: Evidence from a quantile-vector autoregressive approach," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 48(C), pages 178-191.
    26. Dickey, David A & Fuller, Wayne A, 1981. "Likelihood Ratio Statistics for Autoregressive Time Series with a Unit Root," Econometrica, Econometric Society, vol. 49(4), pages 1057-1072, June.
    27. Diego Escobari & Mohammad Jafarinejad, 2019. "Investors’ Uncertainty and Stock Market Risk," Journal of Behavioral Finance, Taylor & Francis Journals, vol. 20(3), pages 304-315, July.
    28. Nicholas Bloom, 2009. "The Impact of Uncertainty Shocks," Econometrica, Econometric Society, vol. 77(3), pages 623-685, May.
    29. Harold Glenn A. Valera & Mark J. Holmes & Gazi Hassan, 2017. "Stock market uncertainty and interest rate behaviour: a panel GARCH approach," Applied Economics Letters, Taylor & Francis Journals, vol. 24(11), pages 732-735, June.
    30. Diebold, Francis X & Mariano, Roberto S, 2002. "Comparing Predictive Accuracy," Journal of Business & Economic Statistics, American Statistical Association, vol. 20(1), pages 134-144, January.
    31. Gupta, Rangan & Ma, Jun & Risse, Marian & Wohar, Mark E., 2018. "Common business cycles and volatilities in US states and MSAs: The role of economic uncertainty," Journal of Macroeconomics, Elsevier, vol. 57(C), pages 317-337.
    32. Daniel Andrei & Michael Hasler, 2015. "Investor Attention and Stock Market Volatility," The Review of Financial Studies, Society for Financial Studies, vol. 28(1), pages 33-72.
    33. John Y. Campbell, 2007. "Estimating the Equity Premium," NBER Working Papers 13423, National Bureau of Economic Research, Inc.
    34. Sydney C. Ludvigson & Sai Ma & Serena Ng, 2021. "Uncertainty and Business Cycles: Exogenous Impulse or Endogenous Response?," American Economic Journal: Macroeconomics, American Economic Association, vol. 13(4), pages 369-410, October.
    35. Ser-Huang Poon & Clive W.J. Granger, 2003. "Forecasting Volatility in Financial Markets: A Review," Journal of Economic Literature, American Economic Association, vol. 41(2), pages 478-539, June.
    36. Su, Zhi & Fang, Tong & Yin, Libo, 2017. "The role of news-based implied volatility among US financial markets," Economics Letters, Elsevier, vol. 157(C), pages 24-27.
    37. William F. Sharpe, 1964. "Capital Asset Prices: A Theory Of Market Equilibrium Under Conditions Of Risk," Journal of Finance, American Finance Association, vol. 19(3), pages 425-442, September.
    38. Benoit Mandelbrot & Adlai Fisher & Laurent Calvet, 1997. "A Multifractal Model of Asset Returns," Cowles Foundation Discussion Papers 1164, Cowles Foundation for Research in Economics, Yale University.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    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. Salisu, Afees A. & Gupta, Rangan & Karmakar, Sayar & Das, Sonali, 2022. "Forecasting output growth of advanced economies over eight centuries: The role of gold market volatility as a proxy of global uncertainty," Resources Policy, Elsevier, vol. 75(C).
    4. 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.
    5. Bonato, Matteo & Cepni, Oguzhan & Gupta, Rangan & Pierdzioch, Christian, 2023. "Climate risks and state-level stock market realized volatility," Journal of Financial Markets, Elsevier, vol. 66(C).
    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. Ruipeng Liu & Rangan Gupta & Elie Bouri, 2021. "Conventional and Unconventional Monetary Policy Rate Uncertainty and Stock Market Volatility: A Forecasting Perspective," Working Papers 202178, University of Pretoria, Department of Economics.
    11. 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).
    12. 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).
    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. Matteo Bonato & Oguzhan Cepni & Rangan Gupta & Christian Pierdzioch, 2024. "Business applications and state‐level stock market realized volatility: A forecasting experiment," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 43(2), pages 456-472, March.
    15. Afees A. Salisu & Riza Demirer & Rangan Gupta, 2023. "Technological Shocks and Stock Market Volatility Over a Century: A GARCH-MIDAS Approach," Working Papers 202308, University of Pretoria, Department of Economics.
    16. 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.
    17. Etaf Alshawarbeh & Alanazi Talal Abdulrahman & Eslam Hussam, 2023. "Statistical Modeling of High Frequency Datasets Using the ARIMA-ANN Hybrid," Mathematics, MDPI, vol. 11(22), pages 1-17, November.
    18. 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.
    19. 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.
    20. Ruipeng Liu & Mawuli Segnon & Oguzhan Cepni & Rangan Gupta, 2023. "Forecasting Volatility of Commodity, Currency, and Stock Markets: Evidence from Markov Switching Multifractal Models," Working Papers 202340, University of Pretoria, Department of Economics.
    21. 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.

    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. Ruipeng Liu & Rangan Gupta & Elie Bouri, 2021. "Conventional and Unconventional Monetary Policy Rate Uncertainty and Stock Market Volatility: A Forecasting Perspective," Working Papers 202178, University of Pretoria, Department of Economics.
    2. Rangan Gupta & Jacobus Nel & Christian Pierdzioch, 2023. "Investor Confidence and Forecastability of US Stock Market Realized Volatility: Evidence from Machine Learning," Journal of Behavioral Finance, Taylor & Francis Journals, vol. 24(1), pages 111-122, January.
    3. Ruipeng Liu & Riza Demirer & Rangan Gupta & Mark Wohar, 2020. "Volatility forecasting with bivariate multifractal models," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 39(2), pages 155-167, March.
    4. Rangan Gupta & Hardik A. Marfatia & Christian Pierdzioch & Afees A. Salisu, 2022. "Machine Learning Predictions of Housing Market Synchronization across US States: The Role of Uncertainty," The Journal of Real Estate Finance and Economics, Springer, vol. 64(4), pages 523-545, May.
    5. Salisu, Afees A. & Gupta, Rangan & Karmakar, Sayar & Das, Sonali, 2022. "Forecasting output growth of advanced economies over eight centuries: The role of gold market volatility as a proxy of global uncertainty," Resources Policy, Elsevier, vol. 75(C).
    6. Segnon, Mawuli & Lux, Thomas, 2013. "Multifractal models in finance: Their origin, properties, and applications," Kiel Working Papers 1860, Kiel Institute for the World Economy (IfW Kiel).
    7. Ruipeng Liu & Riza Demirer & Rangan Gupta & Mark E. Wohar, 2017. "Do Bivariate Multifractal Models Improve Volatility Forecasting in Financial Time Series? An Application to Foreign Exchange and Stock Markets," Working Papers 201728, University of Pretoria, Department of Economics.
    8. Pierdzioch Christian & Gupta Rangan, 2020. "Uncertainty and Forecasts of U.S. Recessions," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 24(4), pages 1-20, September.
    9. Afees A. Salisu & Wenting Liao & Rangan Gupta & Oguzhan Cepni, 2023. "Economic Conditions and Predictability of US Stock Returns Volatility: Local Factor versus National Factor in a GARCH-MIDAS Model," Working Papers 202323, University of Pretoria, Department of Economics.
    10. Diego Escobari & Mohammad Jafarinejad, 2019. "Investors’ Uncertainty and Stock Market Risk," Journal of Behavioral Finance, Taylor & Francis Journals, vol. 20(3), pages 304-315, July.
    11. Salisu, Afees A. & Ogbonna, Ahamuefula E. & Gupta, Rangan & Bouri, Elie, 2024. "Energy-related uncertainty and international stock market volatility," The Quarterly Review of Economics and Finance, Elsevier, vol. 95(C), pages 280-293.
    12. Demirer, Riza & Gupta, Rangan & Salisu, Afees A. & van Eyden, Reneé, 2023. "Firm-level business uncertainty and the predictability of the aggregate U.S. stock market volatility during the COVID-19 pandemic," The Quarterly Review of Economics and Finance, Elsevier, vol. 88(C), pages 295-302.
    13. Plakandaras, Vasilios & Gupta, Rangan & Balcilar, Mehmet & Ji, Qiang, 2022. "Evolving United States stock market volatility: The role of conventional and unconventional monetary policies," The North American Journal of Economics and Finance, Elsevier, vol. 60(C).
    14. Woraphon Yamaka & Rangan Gupta & Sukrit Thongkairat & Paravee Maneejuk, 2023. "Structural and predictive analyses with a mixed copula‐based vector autoregression model," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 42(2), pages 223-239, March.
    15. Mawuli Segnon & Rangan Gupta & Stelios Bekiros & Mark E. Wohar, 2018. "Forecasting US GNP growth: The role of uncertainty," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 37(5), pages 541-559, August.
    16. Hossein Hassani & Mohammad Reza Yeganegi & Rangan Gupta, 2020. "Historical Forecasting Of Interest Rate Mean And Volatility Of The United States: Is There A Role Of Uncertainty?," Annals of Financial Economics (AFE), World Scientific Publishing Co. Pte. Ltd., vol. 15(04), pages 1-17, December.
    17. Rangan Gupta & Yuvana Jaichand & Christian Pierdzioch & Reneé van Eyden, 2023. "Realized Stock-Market Volatility of the United States and the Presidential Approval Rating," Mathematics, MDPI, vol. 11(13), pages 1-27, July.
    18. Wang, Yudong & Wu, Chongfeng & Yang, Li, 2016. "Forecasting crude oil market volatility: A Markov switching multifractal volatility approach," International Journal of Forecasting, Elsevier, vol. 32(1), pages 1-9.
    19. Taylor, Nicholas, 2008. "Can idiosyncratic volatility help forecast stock market volatility?," International Journal of Forecasting, Elsevier, vol. 24(3), pages 462-479.
    20. Andersen, Torben G. & Bollerslev, Tim & Christoffersen, Peter F. & Diebold, Francis X., 2006. "Volatility and Correlation Forecasting," Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.), Handbook of Economic Forecasting, edition 1, volume 1, chapter 15, pages 777-878, Elsevier.

    More about this item

    Statistics

    Access and download statistics

    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:taf:hbhfxx:v:23:y:2022:i:3:p:327-337. 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: Chris Longhurst (email available below). General contact details of provider: http://www.tandfonline.com/hbhf .

    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.