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Exploring the role of the realized return distribution in the formation of the implied volatility smile

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  • Chalamandaris, Georgios
  • Rompolis, Leonidas S.
Abstract
This article explores the role of the realized return distribution in the formation of the observed implied volatility smile using the framework of an adaptive expectations model. According to this framework investors update their expectations of future events, through which options are priced, by incorporating information from the underlying asset traded in the spot market. Our study is conducted at the level of cumulants which provide a complete description of investors expectations and can be considered as largely non-parametric with a minimal set of assumptions for the stochastic process that drives asset returns. The empirical results, based on the S&P 500 index, support the significance of the realized distribution in the formation of the implied volatility smile.

Suggested Citation

  • Chalamandaris, Georgios & Rompolis, Leonidas S., 2012. "Exploring the role of the realized return distribution in the formation of the implied volatility smile," Journal of Banking & Finance, Elsevier, vol. 36(4), pages 1028-1044.
  • Handle: RePEc:eee:jbfina:v:36:y:2012:i:4:p:1028-1044
    DOI: 10.1016/j.jbankfin.2011.10.016
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    as
    1. Guidolin, Massimo & Timmermann, Allan, 2003. "Option prices under Bayesian learning: implied volatility dynamics and predictive densities," Journal of Economic Dynamics and Control, Elsevier, vol. 27(5), pages 717-769, March.
    2. 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.
    3. Stutzer, Michael, 1996. "A Simple Nonparametric Approach to Derivative Security Valuation," Journal of Finance, American Finance Association, vol. 51(5), pages 1633-1652, December.
    4. Kaushik Amin & Joshua D. Coval & H. Nejat Seyhun, 2004. "Index Option Prices and Stock Market Momentum," The Journal of Business, University of Chicago Press, vol. 77(4), pages 835-874, October.
    5. Rosenberg, Joshua V. & Engle, Robert F., 2002. "Empirical pricing kernels," Journal of Financial Economics, Elsevier, vol. 64(3), pages 341-372, June.
    6. Bates, David S, 1996. "Jumps and Stochastic Volatility: Exchange Rate Processes Implicit in Deutsche Mark Options," The Review of Financial Studies, Society for Financial Studies, vol. 9(1), pages 69-107.
    7. repec:bla:jfinan:v:59:y:2004:i:2:p:711-753 is not listed on IDEAS
    8. Glosten, Lawrence R & Jagannathan, Ravi & Runkle, David E, 1993. "On the Relation between the Expected Value and the Volatility of the Nominal Excess Return on Stocks," Journal of Finance, American Finance Association, vol. 48(5), pages 1779-1801, December.
    9. Bollerslev, Tim, 1986. "Generalized autoregressive conditional heteroskedasticity," Journal of Econometrics, Elsevier, vol. 31(3), pages 307-327, April.
    10. Lee, Wayne Y. & Jiang, Christine X. & Indro, Daniel C., 2002. "Stock market volatility, excess returns, and the role of investor sentiment," Journal of Banking & Finance, Elsevier, vol. 26(12), pages 2277-2299.
    11. Ian W. Martin, 2013. "Consumption-Based Asset Pricing with Higher Cumulants," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 80(2), pages 745-773.
    12. Rompolis, Leonidas S. & Tzavalis, Elias, 2008. "Recovering Risk Neutral Densities from Option Prices: A New Approach," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 43(4), pages 1037-1053, December.
    13. Milton Friedman, 1957. "A Theory of the Consumption Function," NBER Books, National Bureau of Economic Research, Inc, number frie57-1.
    14. Gurdip Bakshi & Nikunj Kapadia & Dilip Madan, 2003. "Stock Return Characteristics, Skew Laws, and the Differential Pricing of Individual Equity Options," The Review of Financial Studies, Society for Financial Studies, vol. 16(1), pages 101-143.
    15. Sílvia Gonçalves & Massimo Guidolin, 2006. "Predictable Dynamics in the S&P 500 Index Options Implied Volatility Surface," The Journal of Business, University of Chicago Press, vol. 79(3), pages 1591-1636, May.
    16. Engle, Robert F & Gonzalez-Rivera, Gloria, 1991. "Semiparametric ARCH Models," Journal of Business & Economic Statistics, American Statistical Association, vol. 9(4), pages 345-359, October.
    17. Davidson, James E H, et al, 1978. "Econometric Modelling of the Aggregate Time-Series Relationship between Consumers' Expenditure and Income in the United Kingdom," Economic Journal, Royal Economic Society, vol. 88(352), pages 661-692, December.
    18. Pena, Ignacio & Rubio, Gonzalo & Serna, Gregorio, 1999. "Why do we smile? On the determinants of the implied volatility function," Journal of Banking & Finance, Elsevier, vol. 23(8), pages 1151-1179, August.
    19. Deuskar, Prachi & Gupta, Anurag & Subrahmanyam, Marti G., 2008. "The economic determinants of interest rate option smiles," Journal of Banking & Finance, Elsevier, vol. 32(5), pages 714-728, May.
    20. repec:bla:jfinan:v:59:y:2004:i:1:p:407-446 is not listed on IDEAS
    21. Bing Han, 2008. "Investor Sentiment and Option Prices," The Review of Financial Studies, Society for Financial Studies, vol. 21(1), pages 387-414, January.
    22. Dennis, Patrick & Mayhew, Stewart, 2002. "Risk-Neutral Skewness: Evidence from Stock Options," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 37(3), pages 471-493, September.
    23. Nelson, Daniel B, 1991. "Conditional Heteroskedasticity in Asset Returns: A New Approach," Econometrica, Econometric Society, vol. 59(2), pages 347-370, March.
    24. Ding, Zhuanxin & Granger, Clive W. J. & Engle, Robert F., 1993. "A long memory property of stock market returns and a new model," Journal of Empirical Finance, Elsevier, vol. 1(1), pages 83-106, June.
    25. Milton Friedman, 1957. "Introduction to "A Theory of the Consumption Function"," NBER Chapters, in: A Theory of the Consumption Function, pages 1-6, National Bureau of Economic Research, Inc.
    26. Jackwerth, Jens Carsten, 2000. "Recovering Risk Aversion from Option Prices and Realized Returns," The Review of Financial Studies, Society for Financial Studies, vol. 13(2), pages 433-451.
    27. Diebold, Francis X & Mariano, Roberto S, 2002. "Comparing Predictive Accuracy," Journal of Business & Economic Statistics, American Statistical Association, vol. 20(1), pages 134-144, January.
    28. Heston, Steven L, 1993. "A Closed-Form Solution for Options with Stochastic Volatility with Applications to Bond and Currency Options," The Review of Financial Studies, Society for Financial Studies, vol. 6(2), pages 327-343.
    29. Rockinger, Michael & Jondeau, Eric, 2002. "Entropy densities with an application to autoregressive conditional skewness and kurtosis," Journal of Econometrics, Elsevier, vol. 106(1), pages 119-142, January.
    30. Konstantinidi, Eirini & Skiadopoulos, George & Tzagkaraki, Emilia, 2008. "Can the evolution of implied volatility be forecasted? Evidence from European and US implied volatility indices," Journal of Banking & Finance, Elsevier, vol. 32(11), pages 2401-2411, November.
    31. Campa, Jose M. & Chang, P. H. Kevin & Reider, Robert L., 1998. "Implied exchange rate distributions: evidence from OTC option markets1," Journal of International Money and Finance, Elsevier, vol. 17(1), pages 117-160, February.
    32. Cox, John C. & Ross, Stephen A., 1976. "The valuation of options for alternative stochastic processes," Journal of Financial Economics, Elsevier, vol. 3(1-2), pages 145-166.
    33. Campbell, John Y, 1993. "Intertemporal Asset Pricing without Consumption Data," American Economic Review, American Economic Association, vol. 83(3), pages 487-512, June.
    34. Leonidas S. Rompolis & Elias Tzavalis, 2010. "Risk Premium Effects On Implied Volatility Regressions," Journal of Financial Research, Southern Finance Association;Southwestern Finance Association, vol. 33(2), pages 125-151, June.
    35. Bollerslev, Tim & Zhou, Hao, 2006. "Volatility puzzles: a simple framework for gauging return-volatility regressions," Journal of Econometrics, Elsevier, vol. 131(1-2), pages 123-150.
    36. Giovanni Barone Adesi & Robert F. Engle & Loriano Mancini, 2014. "A GARCH Option Pricing Model with Filtered Historical Simulation," Palgrave Macmillan Books, in: Giovanni Barone Adesi (ed.), Simulating Security Returns: A Filtered Historical Simulation Approach, chapter 4, pages 66-108, Palgrave Macmillan.
    37. Bjørn Eraker & Michael Johannes & Nicholas Polson, 2003. "The Impact of Jumps in Volatility and Returns," Journal of Finance, American Finance Association, vol. 58(3), pages 1269-1300, June.
    38. Ray, Bonnie K & Tsay, Ruey S, 2000. "Long-Range Dependence in Daily Stock Volatilities," Journal of Business & Economic Statistics, American Statistical Association, vol. 18(2), pages 254-262, April.
    39. Bollerslev, Tim & Jubinski, Dan, 1999. "Equity Trading Volume and Volatility: Latent Information Arrivals and Common Long-Run Dependencies," Journal of Business & Economic Statistics, American Statistical Association, vol. 17(1), pages 9-21, January.
    40. Giannopoulos, Kostas & Tunaru, Radu, 2005. "Coherent risk measures under filtered historical simulation," Journal of Banking & Finance, Elsevier, vol. 29(4), pages 979-996, April.
    41. repec:bla:jfinan:v:53:y:1998:i:2:p:499-547 is not listed on IDEAS
    42. Bedendo, Mascia & Hodges, Stewart D., 2009. "The dynamics of the volatility skew: A Kalman filter approach," Journal of Banking & Finance, Elsevier, vol. 33(6), pages 1156-1165, June.
    43. Christensen, B. J. & Prabhala, N. R., 1998. "The relation between implied and realized volatility," Journal of Financial Economics, Elsevier, vol. 50(2), pages 125-150, November.
    44. Rompolis, Leonidas S., 2010. "Retrieving risk neutral densities from European option prices based on the principle of maximum entropy," Journal of Empirical Finance, Elsevier, vol. 17(5), pages 918-937, December.
    45. Bates, David S., 2000. "Post-'87 crash fears in the S&P 500 futures option market," Journal of Econometrics, Elsevier, vol. 94(1-2), pages 181-238.
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    Cited by:

    1. Jarno Talponen, 2018. "Matching distributions: Recovery of implied physical densities from option prices," Papers 1803.03996, arXiv.org.
    2. repec:mod:depeco:0015 is not listed on IDEAS
    3. silvia Muzzioli & Alessio Ruggieri, 2013. "Option Implied Trees and Implied Moments," Department of Economics (DEMB) 0015, University of Modena and Reggio Emilia, Department of Economics "Marco Biagi".
    4. 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.
    5. Liu, Yi-Fang & Zhang, Wei & Xu, Hai-Chuan, 2014. "Collective behavior and options volatility smile: An agent-based explanation," Economic Modelling, Elsevier, vol. 39(C), pages 232-239.

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    More about this item

    Keywords

    Filtered Historical Simulation; Risk-neutral cumulants; Realized cumulants; Adaptive expectations;
    All these keywords.

    JEL classification:

    • G13 - Financial Economics - - General Financial Markets - - - Contingent Pricing; Futures Pricing
    • G14 - Financial Economics - - General Financial Markets - - - Information and Market Efficiency; Event Studies; Insider Trading

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