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An analysis of implied volatility jump dynamics: Novel functional data representation in crude oil markets

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  • Kearney, Fearghal
  • Murphy, Finbarr
  • Cummins, Mark

Abstract

The predominant fear in capital markets is that of a price spike. Commodity markets differ in that there is a fear of both upward and down jumps, this results in implied volatility curves displaying distinct shapes when compared to equity markets. The use of a novel functional data analysis (FDA) approach, provides a framework to produce and interpret functional objects that characterise the underlying dynamics of oil future options. We use the FDA framework to examine implied volatility, jump risk, and pricing dynamics within crude oil markets. Examining a WTI crude oil sample for the 2007–2013 period, which includes the global financial crisis and the Arab Spring, strong evidence is found of converse jump dynamics during periods of demand and supply side weakness. This is used as a basis for an FDA-derived Merton (1976) jump diffusion optimised delta hedging strategy, which exhibits superior portfolio management results over traditional methods.

Suggested Citation

  • Kearney, Fearghal & Murphy, Finbarr & Cummins, Mark, 2015. "An analysis of implied volatility jump dynamics: Novel functional data representation in crude oil markets," The North American Journal of Economics and Finance, Elsevier, vol. 33(C), pages 199-216.
  • Handle: RePEc:eee:ecofin:v:33:y:2015:i:c:p:199-216
    DOI: 10.1016/j.najef.2015.04.006
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    References listed on IDEAS

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    1. Müller, Hans-Georg & Sen, Rituparna & Stadtmüller, Ulrich, 2011. "Functional data analysis for volatility," Journal of Econometrics, Elsevier, vol. 165(2), pages 233-245.
    2. Moschini, GianCarlo & Myers, Robert J., 2002. "Testing for constant hedge ratios in commodity markets: a multivariate GARCH approach," Journal of Empirical Finance, Elsevier, vol. 9(5), pages 589-603, December.
    3. Chang, Chia-Lin & McAleer, Michael & Tansuchat, Roengchai, 2013. "Conditional correlations and volatility spillovers between crude oil and stock index returns," The North American Journal of Economics and Finance, Elsevier, vol. 25(C), pages 116-138.
    4. Anders B. Trolle & Eduardo S. Schwartz, 2009. "Unspanned Stochastic Volatility and the Pricing of Commodity Derivatives," Review of Financial Studies, Society for Financial Studies, vol. 22(11), pages 4423-4461, November.
    5. Bates, David S, 1991. " The Crash of '87: Was It Expected? The Evidence from Options Markets," Journal of Finance, American Finance Association, vol. 46(3), pages 1009-1044, July.
    6. S. Muzzioli, 2010. "Option-based forecasts of volatility: an empirical study in the DAX-index options market," The European Journal of Finance, Taylor & Francis Journals, vol. 16(6), pages 561-586.
    7. Beber, Alessandro & Breedon, Francis & Buraschi, Andrea, 2010. "Differences in beliefs and currency risk premiums," Journal of Financial Economics, Elsevier, vol. 98(3), pages 415-438, December.
    8. Benoit Mandelbrot, 1967. "The Variation of Some Other Speculative Prices," The Journal of Business, University of Chicago Press, vol. 40, pages 393-393.
    9. Charles J. Corrado & Thomas W. Miller, 2006. "Estimating Expected Excess Returns Using Historical And Option-Implied Volatility," Journal of Financial Research, Southern Finance Association;Southwestern Finance Association, vol. 29(1), pages 95-112.
    10. Bakshi, Gurdip & Cao, Charles & Chen, Zhiwu, 1997. " Empirical Performance of Alternative Option Pricing Models," Journal of Finance, American Finance Association, vol. 52(5), pages 2003-2049, December.
    11. Giot, Pierre & Laurent, Sébastien & Petitjean, Mikael, 2010. "Trading activity, realized volatility and jumps," Journal of Empirical Finance, Elsevier, vol. 17(1), pages 168-175, January.
    12. Nomikos, Nikos K. & Soldatos, Orestes A., 2010. "Analysis of model implied volatility for jump diffusion models: Empirical evidence from the Nordpool market," Energy Economics, Elsevier, vol. 32(2), pages 302-312, March.
    13. Askari, Hossein & Krichene, Noureddine, 2008. "Oil price dynamics (2002-2006)," Energy Economics, Elsevier, vol. 30(5), pages 2134-2153, September.
    14. Yan, Shu, 2011. "Jump risk, stock returns, and slope of implied volatility smile," Journal of Financial Economics, Elsevier, vol. 99(1), pages 216-233, January.
    15. Liu, Peng & Tang, Ke, 2011. "The stochastic behavior of commodity prices with heteroskedasticity in the convenience yield," Journal of Empirical Finance, Elsevier, vol. 18(2), pages 211-224, March.
    16. Ball, Clifford A. & Torous, Walter N., 1983. "A Simplified Jump Process for Common Stock Returns," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 18(01), pages 53-65, March.
    17. Neil A. Wilmot and Charles F. Mason, 2013. "Jump Processes in the Market for Crude Oil," The Energy Journal, International Association for Energy Economics, vol. 0(Number 1).
    18. Bates, David S, 1996. "Jumps and Stochastic Volatility: Exchange Rate Processes Implicit in Deutsche Mark Options," Review of Financial Studies, Society for Financial Studies, vol. 9(1), pages 69-107.
    19. Merton, Robert C., 1976. "Option pricing when underlying stock returns are discontinuous," Journal of Financial Economics, Elsevier, vol. 3(1-2), pages 125-144.
    20. Philippe Jorion, 1988. "On Jump Processes in the Foreign Exchange and Stock Markets," Review of Financial Studies, Society for Financial Studies, vol. 1(4), pages 427-445.
    21. John F. Garvey & Liam A. Gallagher, 2012. "The Realised–Implied Volatility Relationship: Recent Empirical Evidence from FTSE‐100 Stocks," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 31(7), pages 639-660, November.
    22. Black, Fischer & Scholes, Myron S, 1973. "The Pricing of Options and Corporate Liabilities," Journal of Political Economy, University of Chicago Press, vol. 81(3), pages 637-654, May-June.
    23. Bannouh, Karim & Martens, Martin & van Dijk, Dick, 2013. "Forecasting volatility with the realized range in the presence of noise and non-trading," The North American Journal of Economics and Finance, Elsevier, vol. 26(C), pages 535-551.
    24. Hammoudeh, Shawkat & Araújo Santos, Paulo & Al-Hassan, Abdullah, 2013. "Downside risk management and VaR-based optimal portfolios for precious metals, oil and stocks," The North American Journal of Economics and Finance, Elsevier, vol. 25(C), pages 318-334.
    25. Taylor, Stephen J. & Yadav, Pradeep K. & Zhang, Yuanyuan, 2010. "The information content of implied volatilities and model-free volatility expectations: Evidence from options written on individual stocks," Journal of Banking & Finance, Elsevier, vol. 34(4), pages 871-881, April.
    26. Chuang, Wen-I & Huang, Teng-Ching & Lin, Bing-Huei, 2013. "Predicting volatility using the Markov-switching multifractal model: Evidence from S&P 100 index and equity options," The North American Journal of Economics and Finance, Elsevier, vol. 25(C), pages 168-187.
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    Cited by:

    1. Nagy, Stanislav, 2017. "Integrated depth for measurable functions and sets," Statistics & Probability Letters, Elsevier, vol. 123(C), pages 165-170.

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