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Predictable dynamics in implied volatility surfaces from OTC currency options

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  • Chalamandaris, Georgios
  • Tsekrekos, Andrianos E.

Abstract

Recent empirical studies report predictable dynamics in the volatility surfaces that are implied by observed index option prices, such as those prescribed by general equilibrium models. Using an extensive data set from the over-the-counter options market, we document similar predictability in the factors that capture the daily variation of surfaces implied by options on 25 different foreign exchange rates. We proceed to demonstrate that simple vector autoregressive specifications for the factors can help produce accurate out-of-sample forecasts of the systematic component of the surface at short horizons. Profitable delta-hedged positions can be set up based on these forecasts; however, profits disappear when typical transaction costs are taken into account and when trading rules on wide segments of the surface are sought.

Suggested Citation

  • Chalamandaris, Georgios & Tsekrekos, Andrianos E., 2010. "Predictable dynamics in implied volatility surfaces from OTC currency options," Journal of Banking & Finance, Elsevier, vol. 34(6), pages 1175-1188, June.
  • Handle: RePEc:eee:jbfina:v:34:y:2010:i:6:p:1175-1188
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    Citations

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    Cited by:

    1. Dunis, Christian & Kellard, Neil M. & Snaith, Stuart, 2013. "Forecasting EUR–USD implied volatility: The case of intraday data," Journal of Banking & Finance, Elsevier, vol. 37(12), pages 4943-4957.
    2. Da Fonseca, José & Gottschalk, Katrin, 2014. "Cross-hedging strategies between CDS spreads and option volatility during crises," Journal of International Money and Finance, Elsevier, vol. 49(PB), pages 386-400.
    3. Georgios Chalamandaris & Andrianos Tsekrekos, 2013. "Explanatory Factors and Causality in the Dynamics of Volatility Surfaces Implied from OTC Asian–Pacific Currency Options," Computational Economics, Springer;Society for Computational Economics, vol. 41(3), pages 327-358, March.
    4. Branger, Nicole & Muck, Matthias, 2012. "Keep on smiling? The pricing of Quanto options when all covariances are stochastic," Journal of Banking & Finance, Elsevier, vol. 36(6), pages 1577-1591.
    5. Tanha, Hassan & Dempsey, Michael, 2016. "The evolving dynamics of the Australian SPI 200 implied volatility surface," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 43(C), pages 44-57.
    6. Shackleton, Mark B. & Taylor, Stephen J. & Yu, Peng, 2010. "A multi-horizon comparison of density forecasts for the S&P 500 using index returns and option prices," Journal of Banking & Finance, Elsevier, vol. 34(11), pages 2678-2693, November.
    7. Bernales, Alejandro & Guidolin, Massimo, 2014. "Can we forecast the implied volatility surface dynamics of equity options? Predictability and economic value tests," Journal of Banking & Finance, Elsevier, vol. 46(C), pages 326-342.
    8. Bernales, Alejandro & Guidolin, Massimo, 2015. "Learning to smile: Can rational learning explain predictable dynamics in the implied volatility surface?," Journal of Financial Markets, Elsevier, vol. 26(C), pages 1-37.
    9. Michel van der Wel & Sait R. Ozturk & Dick van Dijk, 2016. "Dynamic Factor Models for the Volatility Surface," Advances in Econometrics,in: Dynamic Factor Models, volume 35, pages 127-174 Emerald Publishing Ltd.
    10. Guo, Biao & Han, Qian & Lin, Hai, 2015. "Forecasting the Term Structure of Implied Volatilities," Working Paper Series 6189, Victoria University of Wellington, School of Economics and Finance.
    11. repec:eee:ecmode:v:64:y:2017:i:c:p:295-301 is not listed on IDEAS

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