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Tradability, closeness to market prices, and expected profit: their measurement for a binomial model of options pricing in a heterogeneous market

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  • Yossi Shvimer

    (Bar-Ilan University)

  • Avi Herbon

    (Bar-Ilan University)

Abstract

A reliable method of options pricing in real time would help various players, including hedgers and speculators, to make informed decisions. In this study, we develop an extensive simulation with multiple business environments, which includes the use of real data from the S&P 500 Index between the years 2010–2017 for the 30 days prior to expiration of the options. Forecasted tradability is computed based on the SH model: a theoretical model of real-time options pricing that takes into account players’ heterogeneity with regard to their willingness to accept offers proposed by the opposing player. The quality of the model is examined for the scenario in which the model players are speculators who act against the real market prices. We show that the equilibrium prices predicted by the SH model are close to the market prices (a deviation of up to approx. 3%) in an In-The-Money environment. Additionally, the tougher the players (i.e., the greater their level of unwillingness to accept a bid from the opposing player), the higher the average tradability. We also find that the level of willingness of the players has a greater effect on tradability than does option moneyness or the market trend.

Suggested Citation

  • Yossi Shvimer & Avi Herbon, 2020. "Tradability, closeness to market prices, and expected profit: their measurement for a binomial model of options pricing in a heterogeneous market," Journal of Economic Interaction and Coordination, Springer;Society for Economic Science with Heterogeneous Interacting Agents, vol. 15(3), pages 737-762, July.
    • Handle: RePEc:spr:jeicoo:v:15:y:2020:i:3:d:10.1007_s11403-019-00259-0
    DOI: 10.1007/s11403-019-00259-0
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    1. León, à ngel & Mencía, Javier & Sentana, Enrique, 2009. "Parametric Properties of Semi-Nonparametric Distributions, with Applications to Option Valuation," Journal of Business & Economic Statistics, American Statistical Association, vol. 27(2), pages 176-192.
    2. U. Çetin & R. Jarrow & P. Protter & M. Warachka, 2008. "Pricing Options in an Extended Black Scholes Economy with Illiquidity: Theory and Empirical Evidence," World Scientific Book Chapters, in: Financial Derivatives Pricing Selected Works of Robert Jarrow, chapter 9, pages 185-221, World Scientific Publishing Co. Pte. Ltd..
    3. Zhenxi Chen & Thomas Lux, 2018. "Estimation of Sentiment Effects in Financial Markets: A Simulated Method of Moments Approach," Computational Economics, Springer;Society for Computational Economics, vol. 52(3), pages 711-744, October.
    4. James S. Doran & Andy Fodor & Kevin Krieger, 2010. "Option Market Efficiency and Analyst Recommendations," Journal of Business Finance & Accounting, Wiley Blackwell, vol. 37(5-6), pages 560-590.
    5. Rosenberg, Joshua V. & Engle, Robert F., 2002. "Empirical pricing kernels," Journal of Financial Economics, Elsevier, vol. 64(3), pages 341-372, June.
    6. Nicolas P. B. Bollen & Robert E. Whaley, 2004. "Does Net Buying Pressure Affect the Shape of Implied Volatility Functions?," Journal of Finance, American Finance Association, vol. 59(2), pages 711-753, April.
    7. Xiaoyan Ni, Sophie & Pearson, Neil D. & Poteshman, Allen M., 2005. "Stock price clustering on option expiration dates," Journal of Financial Economics, Elsevier, vol. 78(1), pages 49-87, October.
    8. Robin K. Chou & San‐Lin Chung & Yu‐Jen Hsiao & Yaw‐Huei Wang, 2011. "The impact of liquidity on option prices," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 31(12), pages 1116-1141, December.
    9. James S. Doran & Andy Fodor & Kevin Krieger, 2010. "Option Market Efficiency and Analyst Recommendations," Journal of Business Finance & Accounting, Wiley Blackwell, vol. 37(5‐6), pages 560-590, June.
    10. Young-Hye Cho & Robert F. Engle, 1999. "Time-Varying Betas and Asymmetric Effect of News: Empirical Analysis of Blue Chip Stocks," NBER Working Papers 7330, National Bureau of Economic Research, Inc.
    11. Marco Avellaneda & Michael Lipkin, 2003. "A market-induced mechanism for stock pinning," Quantitative Finance, Taylor & Francis Journals, vol. 3(6), pages 417-425.
    12. Brandt, Michael W. & Wu, Tao, 2002. "Cross-sectional tests of deterministic volatility functions," Journal of Empirical Finance, Elsevier, vol. 9(5), pages 525-550, December.
    13. Olivier Compte & Philippe Jehiel, 2004. "The Wait-and-See Option in Ascending Price Auctions," Journal of the European Economic Association, MIT Press, vol. 2(2-3), pages 494-503, 04/05.
    14. Fedenia, Mark & Grammatikos, Theoharry, 1992. "Options Trading and the Bid-Ask Spread of the Underlying Stocks," The Journal of Business, University of Chicago Press, vol. 65(3), pages 335-351, July.
    15. Golez, Benjamin & Jackwerth, Jens Carsten, 2012. "Pinning in the S&P 500 futures," Journal of Financial Economics, Elsevier, vol. 106(3), pages 566-585.
    16. Jang, H. & Lee, J., 2019. "Machine learning versus econometric jump models in predictability and domain adaptability of index options," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 513(C), pages 74-86.
    17. Andrea Buraschi & Alexei Jiltsov, 2006. "Model Uncertainty and Option Markets with Heterogeneous Beliefs," Journal of Finance, American Finance Association, vol. 61(6), pages 2841-2897, December.
    18. Charilaos E. Linaras & George Skiadopoulos, 2005. "Implied Volatility Trees And Pricing Performance: Evidence From The S&P 100 Options," International Journal of Theoretical and Applied Finance (IJTAF), World Scientific Publishing Co. Pte. Ltd., vol. 8(08), pages 1085-1106.
    19. Cox, John C. & Ross, Stephen A. & Rubinstein, Mark, 1979. "Option pricing: A simplified approach," Journal of Financial Economics, Elsevier, vol. 7(3), pages 229-263, September.
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