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A grey-based correlation with multi-scale analysis: S&P 500 VIX and individual VIXs of large US company stocks

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  • Wang, Zhenkun
  • Bouri, Elie
  • Ferreira, Paulo
  • Shahzad, Syed Jawad Hussain
  • Ferrer, Román

Abstract

We provide first evidence of the multiscale comovement of correlations between the S&P 500 VIX and the VIXs of Amazon, Apple, Google, Goldman Sachs, and IBM. Using grey correlation and wavelet analysis on daily data (July 2011 - September 2021), the dynamics of grey-based correlations vary across scales and depend on the fluctuation intensity of the medium time–frequency domains. The lead–lag relationships of VIX correlations are inconclusive about the dominant periodicity, although some evidence of weekly and monthly periodicity emerges. The pandemic affects the dynamics and lead-lag relationships. Such indications are useful for trading strategies and market-timing decisions.

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  • Wang, Zhenkun & Bouri, Elie & Ferreira, Paulo & Shahzad, Syed Jawad Hussain & Ferrer, Román, 2022. "A grey-based correlation with multi-scale analysis: S&P 500 VIX and individual VIXs of large US company stocks," Finance Research Letters, Elsevier, vol. 48(C).
    • Handle: RePEc:eee:finlet:v:48:y:2022:i:c:s154461232200157x
    DOI: 10.1016/j.frl.2022.102872
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    References listed on IDEAS

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    1. Qadan, Mahmoud & Kliger, Doron & Chen, Nir, 2019. "Idiosyncratic volatility, the VIX and stock returns," The North American Journal of Economics and Finance, Elsevier, vol. 47(C), pages 431-441.
    2. Fernandes, Marcelo & Medeiros, Marcelo C. & Scharth, Marcel, 2014. "Modeling and predicting the CBOE market volatility index," Journal of Banking & Finance, Elsevier, vol. 40(C), pages 1-10.
    3. Bouri, Elie & Lucey, Brian & Roubaud, David, 2020. "Dynamics and determinants of spillovers across the option-implied volatilities of US equities," The Quarterly Review of Economics and Finance, Elsevier, vol. 75(C), pages 257-264.
    4. Li, Leon, 2022. "The dynamic interrelations of oil-equity implied volatility indexes under low and high volatility-of-volatility risk," Energy Economics, Elsevier, vol. 105(C).
    5. Bikramaditya Ghosh & Elie Bouri & Andreas Pape, 2022. "Long Memory and Fractality in the Universe of Volatility Indices," Complexity, Hindawi, vol. 2022, pages 1-8, January.
    6. Jiang, Meihui & An, Haizhong & Jia, Xiaoliang & Sun, Xiaoqi, 2017. "The influence of global benchmark oil prices on the regional oil spot market in multi-period evolution," Energy, Elsevier, vol. 118(C), pages 742-752.
    7. Jia, Xiaoliang & An, Haizhong & Fang, Wei & Sun, Xiaoqi & Huang, Xuan, 2015. "How do correlations of crude oil prices co-move? A grey correlation-based wavelet perspective," Energy Economics, Elsevier, vol. 49(C), pages 588-598.
    8. DIMA, Bogdan & DIMA, Ştefana Maria & IOAN, Roxana, 2021. "Remarks on the behaviour of financial market efficiency during the COVID-19 pandemic. The case of VIX," Finance Research Letters, Elsevier, vol. 43(C).
    9. Celeste, Valerio & Corbet, Shaen & Gurdgiev, Constantin, 2020. "Fractal dynamics and wavelet analysis: Deep volatility and return properties of Bitcoin, Ethereum and Ripple," The Quarterly Review of Economics and Finance, Elsevier, vol. 76(C), pages 310-324.
    10. Tiwari, Aviral Kumar & Jana, R.K. & Roubaud, David, 2019. "The policy uncertainty and market volatility puzzle: Evidence from wavelet analysis," Finance Research Letters, Elsevier, vol. 31(C).
    11. Gonzalez-Perez, Maria T., 2015. "Model-free volatility indexes in the financial literature: A review," International Review of Economics & Finance, Elsevier, vol. 40(C), pages 141-159.
    12. Ji, Qiang & Bouri, Elie & Roubaud, David, 2018. "Dynamic network of implied volatility transmission among US equities, strategic commodities, and BRICS equities," International Review of Financial Analysis, Elsevier, vol. 57(C), pages 1-12.
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    Cited by:

    1. Kristoufek, Ladislav & Bouri, Elie, 2023. "Exploring sources of statistical arbitrage opportunities among Bitcoin exchanges," Finance Research Letters, Elsevier, vol. 51(C).
    2. Bossman, Ahmed & Gubareva, Mariya & Teplova, Tamara, 2023. "EU sectoral stocks amid geopolitical risk, market sentiment, and crude oil implied volatility: An asymmetric analysis of the Russia-Ukraine tensions," Resources Policy, Elsevier, vol. 82(C).

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