Market expectation shifts in option-implied volatilities in the US and UK stock markets during the Brexit vote


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This paper investigates the effect of the Brexit vote on the connection between UK stock market expectations and US stock market returns. To gauge UK stock market expectations, the option-implied volatilities of the FTSE 100 index are calculated in the period starting five months before and ending four months after the Brexit referendum. To keep the analysis “clean”, it stops right before the 2016 US presidential elections. It uses an OLS regression to estimate the change in the relationship between US and UK stock market expectations.
The main findings show that the US and UK stock markets became somewhat less integrated four months after the Brexit referendum compared to the five months before it. The S&P 500 Index returns have a statistically significant impact on implied volatilities of the FTSE 100 only before the Brexit referendum. However, the British risk-free rate (LIBOR) became a statistically significant factor affecting FTSE 100 implied volatilities only after Brexit. This analysis may be used by decision-makers in the money management industry to act appropriately during Black Swan events. When UK citizens unexpectedly voted in favor of Brexit, the risk-free rate dropped, making it cheaper to invest, increasing the Sharpe ratios of equity portfolios. Coupled with increased uncertainty, this caused portfolio reallocations. In turn, expected volatility measured by options-implied volatility increased.

The authors would like to thank Olesia Verchenko for critique, a KSE M.A., external defense reviewer for helpful comments.

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    • Figure 1. S&P500 Index prices and Volatility Index (VIX)
    • Figure 2. Implied volatility (IV) values in February – October 2016
    • Table 1. Granger causality Wald test
    • Table 2. Model estimation results
    • Table 3. Correlation among model variables
    • Table A1. Dickey-Fuller tests
    • Table A2. Vector autoregressive model results
    • Conceptualization
      Artem Bielykh, Sergiy Pysarenko
    • Data curation
      Artem Bielykh
    • Formal Analysis
      Artem Bielykh, Oleksandr Kubatko
    • Investigation
      Artem Bielykh, Dong Meng Ren, Oleksandr Kubatko
    • Methodology
      Artem Bielykh
    • Software
      Artem Bielykh, Sergiy Pysarenko
    • Writing – original draft
      Artem Bielykh, Sergiy Pysarenko
    • Funding acquisition
      Sergiy Pysarenko
    • Project administration
      Sergiy Pysarenko
    • Resources
      Sergiy Pysarenko
    • Supervision
      Sergiy Pysarenko
    • Writing – review & editing
      Sergiy Pysarenko, Dong Meng Ren, Oleksandr Kubatko
    • Validation
      Dong Meng Ren, Oleksandr Kubatko
    • Visualization
      Dong Meng Ren, Oleksandr Kubatko