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Equity Market Volatility Impact On S&P 500 Sector Indexes, 1989-2021

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  • SOSA-CASTRO, Miriam

Abstract

This paper analyzes the relationship between the Equity Market Volatility Index and the nine S&P 500 sectors indexes, as well as investigating which of the 42 category-specific Equity Market Volatility (EMV) trackers has a greater impact on each sector index. To achieve this purpose, ARDL and NARDL models are proposed to measure the sector index response to EMV index. To examine which categories of EMV trackers most influence the dynamics of each sector index, an artificial neural network is employed. Findings suggest that there is a symmetric, negative, and significant impact of the EMV on all sector indexes. Energy, materials, and financials are the sectors most sensitive to changes in EMV. The ANN results demonstrate that EMV Categorical Trackers describe accurately the sector indexes return. Although each sector reacts to different categories, the factors that affect two or more sectors are: commodity markets, financial regulation, exchange rates, and trade policy.

Suggested Citation

  • SOSA-CASTRO, Miriam, 2022. "Equity Market Volatility Impact On S&P 500 Sector Indexes, 1989-2021," Applied Econometrics and International Development, Euro-American Association of Economic Development, vol. 22(1), pages 39-60.
  • Handle: RePEc:eaa:aeinde:v:22:y:2022:i:1_3
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    1. Robert F. Engle & Jose Gonzalo Rangel, 2008. "The Spline-GARCH Model for Low-Frequency Volatility and Its Global Macroeconomic Causes," Review of Financial Studies, Society for Financial Studies, vol. 21(3), pages 1187-1222, May.
    2. Campbell, John Y. & Hentschel, Ludger, 1992. "No news is good news *1: An asymmetric model of changing volatility in stock returns," Journal of Financial Economics, Elsevier, vol. 31(3), pages 281-318, June.
    3. Chia-Lin Chang & Tai-Lin Hsieh & Michael McAleer, 2018. "Connecting VIX and Stock Index ETF with VAR and Diagonal BEKK," JRFM, MDPI, vol. 11(4), pages 1-25, September.
    4. Chia-Lin Chang & Tai-Lin Hsieh & Michael McAleer, 2016. "How are VIX and Stock Index ETF Related?," Documentos de Trabajo del ICAE 2016-02, Universidad Complutense de Madrid, Facultad de Ciencias Económicas y Empresariales, Instituto Complutense de Análisis Económico.
    5. Dutta, Anupam & Nikkinen, Jussi & Rothovius, Timo, 2017. "Impact of oil price uncertainty on Middle East and African stock markets," Energy, Elsevier, vol. 123(C), pages 189-197.
    6. Muradoğlu, Yaz Gülnur & Sivaprasad, Sheeja, 2012. "Capital structure and abnormal returns," International Business Review, Elsevier, vol. 21(3), pages 328-341.
    7. Hamilton, James D & Gang, Lin, 1996. "Stock Market Volatility and the Business Cycle," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 11(5), pages 573-593, Sept.-Oct.
    8. Massaporn Cheuathonghua & Chaiyuth Padungsaksawasdi & Pattana Boonchoo & Jittima Tongurai, 2019. "Extreme spillovers of VIX fear index to international equity markets," Financial Markets and Portfolio Management, Springer;Swiss Society for Financial Market Research, vol. 33(1), pages 1-38, March.
    9. French, Kenneth R. & Schwert, G. William & Stambaugh, Robert F., 1987. "Expected stock returns and volatility," Journal of Financial Economics, Elsevier, vol. 19(1), pages 3-29, September.
    10. Daniel J. Tulloch & Ivan Diaz-Rainey & I.M Premachandra, 2018. "The impact of regulatory change on EU energy utility returns: the three liberalization packages," Applied Economics, Taylor & Francis Journals, vol. 50(9), pages 957-972, February.
    11. Robert F. Engle & Eric Ghysels & Bumjean Sohn, 2013. "Stock Market Volatility and Macroeconomic Fundamentals," The Review of Economics and Statistics, MIT Press, vol. 95(3), pages 776-797, July.
    12. Dutta, Anupam & Bouri, Elie & Saeed, Tareq, 2021. "News-based equity market uncertainty and crude oil volatility," Energy, Elsevier, vol. 222(C).
    13. Feng, Sida & Huang, Shupei & Qi, Yabin & Liu, Xueyong & Sun, Qingru & Wen, Shaobo, 2018. "Network features of sector indexes spillover effects in China: A multi-scale view," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 496(C), pages 461-473.
    14. Timothy J. Considine, 1991. "Economic and Technological Determinants of the Material Intensity of Use," Land Economics, University of Wisconsin Press, vol. 67(1), pages 99-115.
    15. Hossein Asgharian & Ai Jun Hou & Farrukh Javed, 2013. "The Importance of the Macroeconomic Variables in Forecasting Stock Return Variance: A GARCH‐MIDAS Approach," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 32(7), pages 600-612, November.
    16. Scott R Baker & Nicholas Bloom & Steven J Davis & Kyle Kost & Marco Sammon & Tasaneeya Viratyosin & Jeffrey Pontiff, 0. "The Unprecedented Stock Market Reaction to COVID-19," The Review of Asset Pricing Studies, Society for Financial Studies, vol. 10(4), pages 742-758.
    17. Zhu, Sha & Liu, Qiuhong & Wang, Yan & Wei, Yu & Wei, Guiwu, 2019. "Which fear index matters for predicting US stock market volatilities: Text-counts or option based measurement?," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 536(C).
    18. Abdullah Alqahtani & Michael J. Wither & Zhankui Dong & Kimberly R. Goodwin, 2020. "Impact of news-based equity market volatility on international stock markets," Journal of Applied Economics, Taylor & Francis Journals, vol. 23(1), pages 224-234, January.
    19. Charlie Karlsson & Martin Andersson & Therese Norman (ed.), 2015. "Handbook of Research Methods and Applications in Economic Geography," Books, Edward Elgar Publishing, number 14395.
    20. Scott R. Baker & Nicholas Bloom & Steven J. Davis & Kyle J. Kost, 2019. "Policy News and Stock Market Volatility," NBER Working Papers 25720, National Bureau of Economic Research, Inc.
    21. Hoang, Trang Cam & Pham, Huy & Ramiah, Vikash & Moosa, Imad & Le, Danh Vinh, 2020. "The effects of information disclosure regulation on stock markets: Evidence from Vietnam," Research in International Business and Finance, Elsevier, vol. 51(C).
    22. Huy Nguyen Anh Pham & Vikash Ramiah & Imad Moosa, 2020. "The effects of environmental regulation on the stock market: the French experience," Accounting and Finance, Accounting and Finance Association of Australia and New Zealand, vol. 60(4), pages 3279-3304, December.
    23. Alex Edmans & Lucius Li & Chendi Zhang, 2014. "Employee Satisfaction, Labor Market Flexibility, and Stock Returns Around The World," NBER Working Papers 20300, National Bureau of Economic Research, Inc.
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    More about this item

    Keywords

    S&P 500 Indexes; Equity market.;

    JEL classification:

    • C58 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Financial Econometrics
    • G11 - Financial Economics - - General Financial Markets - - - Portfolio Choice; Investment Decisions
    • D87 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Neuroeconomics
    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes

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