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The Impact of the U.S. Macroeconomic Variables on the CBOE VIX Index

Author

Listed:
  • Akhilesh Prasad

    (SP Jain School of Global Management, Mumbai 400070, India)

  • Priti Bakhshi

    (SP Jain School of Global Management, Mumbai 400070, India)

  • Arumugam Seetharaman

    (SP Jain School of Global Management, Hyderabad Road, Singapore 119579, Singapore)

Abstract

The purpose of this study is to find the influence of various macroeconomic factors on the volatility index, as macroeconomic factors affect stock market volatility, resulting in an impact on the VIX Index, representing the risk in the stock market. To estimate the significance and importance of the U.S. macroeconomic variables on stock market volatility and risk, classification problems from machine learning are constructed to predict the daily and weekly trends of the VIX Index. Data from May 2007 to December 2021 is considered for analysis. The selected models are trained with twenty-four daily features and twenty-four plus nine weekly features. The outcomes suggest that the decisions made by the Light GBM and XG Boost on ranking features can be significantly accepted over logistic regression. It is found from the results that economic policy uncertainty indices, gold price, the USD Index, and crude oil are signified as strong predictors. The Financial Stress Index, initial claims, M2, TED spread, Fed rate, and credit spread are also strong predictors, while various yields on fixed income securities make a little less impact on the VIX Index. The TED spread, Financial Stress Index, and Equity Market Volatility (Infectious Disease Tracker) are positively associated with the VIX.

Suggested Citation

  • Akhilesh Prasad & Priti Bakhshi & Arumugam Seetharaman, 2022. "The Impact of the U.S. Macroeconomic Variables on the CBOE VIX Index," JRFM, MDPI, vol. 15(3), pages 1-25, March.
    • Handle: RePEc:gam:jjrfmx:v:15:y:2022:i:3:p:126-:d:765501
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    References listed on IDEAS

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    Cited by:

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    2. Wang, Mei-Chih & Chang, Tsangyao & Mikhaylov, Alexey & Linyu, Jia, 2024. "A measure of quantile-on-quantile connectedness for the US treasury yield curve spread, the US Dollar, and gold price," The North American Journal of Economics and Finance, Elsevier, vol. 74(C).
    3. Chen, Ruoyu & Iqbal, Najaf & Irfan, Muhammad & Shahzad, Farrukh & Fareed, Zeeshan, 2022. "Does financial stress wreak havoc on banking, insurance, oil, and gold markets? New empirics from the extended joint connectedness of TVP-VAR model," Resources Policy, Elsevier, vol. 77(C).
    4. Pedro M. Nogueira Reis, 2022. "Determinants of Qualified Investor Sentiment during the COVID-19 Pandemic in North America, Asia, and Europe," Economies, MDPI, vol. 10(6), pages 1-20, June.

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