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VIX and volatility forecasting: A new insight

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  • Wang, Hui

Abstract

This study uses a new fresh look to investigate the linkages between the CBOE VIX and stock market volatility. In this paper, we use 13 stock markets of the G20 to do our research and document several important findings. First, in most countries, the VIX and its large component have statistically significant effect and can lead to high stock market volatility. Compared to the R-squares, we find that large VIX has stronger explanation ability to the international stock markets volatility. Second, out-of-sample results indicate that the VIX can help to increase the forecasts accuracy, especially the large VIX. Additionally, the robust tests support our main conclusions.

Suggested Citation

  • Wang, Hui, 2019. "VIX and volatility forecasting: A new insight," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 533(C).
  • Handle: RePEc:eee:phsmap:v:533:y:2019:i:c:s0378437119311392
    DOI: 10.1016/j.physa.2019.121951
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    Citations

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    Cited by:

    1. Zhu, Xuehong & Chen, Ying & Chen, Jinyu, 2021. "Effects of non-ferrous metal prices and uncertainty on industry stock market under different market conditions," Resources Policy, Elsevier, vol. 73(C).
    2. Zeng, Ting & Yang, Mengying & Shen, Yifan, 2020. "Fancy Bitcoin and conventional financial assets: Measuring market integration based on connectedness networks," Economic Modelling, Elsevier, vol. 90(C), pages 209-220.
    3. Szczygielski, Jan Jakub & Charteris, Ailie & Obojska, Lidia & Brzeszczyński, Janusz, 2024. "Capturing the timing of crisis evolution: A machine learning and directional wavelet coherence approach to isolating event-specific uncertainty using Google searches with an application to COVID-19," Technological Forecasting and Social Change, Elsevier, vol. 205(C).
    4. Saffet Akdag & Ömer İskenderoglu & Andrew Adewale Alola, 2020. "The volatility spillover effects among risk appetite indexes: insight from the VIX and the rise," Letters in Spatial and Resource Sciences, Springer, vol. 13(1), pages 49-65, April.
    5. 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.
    6. Korkusuz, Burak & Kambouroudis, Dimos & McMillan, David G., 2023. "Do extreme range estimators improve realized volatility forecasts? Evidence from G7 Stock Markets," Finance Research Letters, Elsevier, vol. 55(PB).
    7. Chow, Yee Peng & Muhammad, Junaina & Bany-Ariffin, A.N. & Cheng, Fan Fah, 2019. "Macroeconomic Uncertainty and Corporate Capital Structure: Evidence from the Asia Pacific Region," Jurnal Ekonomi Malaysia, Faculty of Economics and Business, Universiti Kebangsaan Malaysia, vol. 53(2), pages 99-122.
    8. Luu Duc Huynh, Toan, 2020. "The effect of uncertainty on the precious metals market: New insights from Transfer Entropy and Neural Network VAR," Resources Policy, Elsevier, vol. 66(C).
    9. Salisu, Afees A. & Vo, Xuan Vinh, 2020. "Predicting stock returns in the presence of COVID-19 pandemic: The role of health news," International Review of Financial Analysis, Elsevier, vol. 71(C).
    10. Nicolás Magner Pulgar & Esteban José Antonio Terán Sánchez & Vicente Alfonso Guzmán Muñoz, 2022. "Stock Market Synchronization and Stock Volatility: The Case of an Emerging Market," Remef - Revista Mexicana de Economía y Finanzas Nueva Época REMEF (The Mexican Journal of Economics and Finance), Instituto Mexicano de Ejecutivos de Finanzas, IMEF, vol. 17(3), pages 1-22, Julio - S.
    11. Aljohani, Bader M. & Fadul, Abubaker & Asiri, Maram S. & Alkhathami, Abdulrahman D. & Hasan, Fakhrul, 2024. "Volatility transmission in the property market during two inflationary periods: The 2008–2009 global financial crisis and the COVID-19 crisis," Research in International Business and Finance, Elsevier, vol. 70(PB).
    12. Chen, Zhonglu & Liang, Chao & Umar, Muhammad, 2021. "Is investor sentiment stronger than VIX and uncertainty indices in predicting energy volatility?," Resources Policy, Elsevier, vol. 74(C).
    13. Su, Yuandong & Liang, Chao & Zhang, Li & Zeng, Qing, 2022. "Uncover the response of the U.S grain commodity market on El Niño–Southern Oscillation," International Review of Economics & Finance, Elsevier, vol. 81(C), pages 98-112.

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