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On the Relationship between Economic Policy Uncertainty and the Implied Volatility Index

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  • Imlak Shaikh

    (Department of Accounting and Finance, Management Development Institute Gurgaon, Gurugram 122001, Haryana, India)

Abstract

This article examines the effects of economic policy uncertainty (EPU) on the implied volatility index. The implied volatility index of various markets has been analyzed in relation to scheduled macroeconomic announcements, such as EPU and equity market policy uncertainty (EMPU) indices. The study highlights that EPU contains important information to explain the diverse market effects of the U.S., which is gauged into the volatility index. Estimates obtained in an autoregressive conditional heteroscedasticity framework indicate the persistence of volatility during spikes in the EPU. More importantly, the lagged values of the policy uncertainty index also contains market-related information to explain the markets’ future volatility. Major political and economic events have also contributed positively in that a presidential election contains information to explain various asset classes. Commodities, such as crude oil, gold, corn, and soybean, have been impacted significantly followed by EPU. Moreover, interest rate market volatility has also been moved adversely due to tight monetary policy. The Markov regime switching regression manifests that the implied volatility index (VIX) behaves abruptly in two different regimes followed by EPU.

Suggested Citation

  • Imlak Shaikh, 2019. "On the Relationship between Economic Policy Uncertainty and the Implied Volatility Index," Sustainability, MDPI, vol. 11(6), pages 1-11, March.
    • Handle: RePEc:gam:jsusta:v:11:y:2019:i:6:p:1628-:d:214829
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    2. Imlak Shaikh, 2019. "The U.S. Presidential Election 2012/2016 and Investors’ Sentiment: The Case of CBOE Market Volatility Index," SAGE Open, , vol. 9(3), pages 21582440198, July.
    3. Haddou, Samira, 2024. "Determinants of CDS in core and peripheral European countries: A comparative study during crisis and calm periods," The North American Journal of Economics and Finance, Elsevier, vol. 71(C).
    4. Guan, Jialin & Xu, Huijuan & Huo, Da & Hua, Yechun & Wang, Yunfeng, 2021. "Economic policy uncertainty and corporate innovation: Evidence from China," Pacific-Basin Finance Journal, Elsevier, vol. 67(C).
    5. Wang, Jiqian & Lu, Xinjie & He, Feng & Ma, Feng, 2020. "Which popular predictor is more useful to forecast international stock markets during the coronavirus pandemic: VIX vs EPU?," International Review of Financial Analysis, Elsevier, vol. 72(C).
    6. Pogorelova, Polina, 2024. "Investigation of the impact of uncertainty indices on Bitcoin volatility using the ARDL model," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 74, pages 35-50.
    7. Yang, Kun & Wei, Yu & Li, Shouwei & Liu, Liang & Wang, Lei, 2021. "Global financial uncertainties and China’s crude oil futures market: Evidence from interday and intraday price dynamics," Energy Economics, Elsevier, vol. 96(C).
    8. Oscar V. De la Torre-Torres & Francisco Venegas-Martínez & Mᵃ Isabel Martínez-Torre-Enciso, 2021. "Enhancing Portfolio Performance and VIX Futures Trading Timing with Markov-Switching GARCH Models," Mathematics, MDPI, vol. 9(2), pages 1-22, January.
    9. Frank, Johannes, 2023. "Forecasting realized volatility in turbulent times using temporal fusion transformers," FAU Discussion Papers in Economics 03/2023, Friedrich-Alexander University Erlangen-Nuremberg, Institute for Economics.

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