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Does Stock Return Predictability Affect ESO Fair Value?

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  • CARMONA, JULIO

    (Universidad de Alicante, Departamento de Métodos Cuantitativos y Teoría Económica)

  • LEÓN, ANGEL

    (Universidad de Alicante, Departamento de Métodos Cuantitativos y Teoría Económica)

  • VAELLO-SEBASTIÁ, ANTONI

    (University of Balear Islands. Dept. Economía de la Empresa)

Abstract

Executive Stock Options (ESOs) are modified American options that cannot be valued using standard methods. With a few exceptions, the literature has discussed the ESO fair value by assuming unpredictable stock returns which are not supported by the available empirical evidence. In this paper we obtain the fair value of American ESOs when stock returns are predictable and, specifically, driven by the trending Ornstein-Uhlenbeck process of Lo and Wang (1995). We solve the executive’s portfolio allocation problem for a simple buy-and-hold strategy when his wealth can be distributed between a risk-free asset and a market portfolio. This problem is jointly solved with the executive’s optimal exercise policy. We find that executives tend to wait longer the higher the predictability, independently of the composition of executive’s asset menu. We have also analyzed the implications under the FAS123R proposals for the ESO fair value and found that, even for low autocorrelations, there is a meaningful mispricing when unpredictable returns are erroneously assumed.

Suggested Citation

  • Carmona, Julio & León, Angel & Vaello-Sebastiá, Antoni, 2011. "Does Stock Return Predictability Affect ESO Fair Value?," QM&ET Working Papers 11-2, University of Alicante, D. Quantitative Methods and Economic Theory, revised 16 Jan 2012.
  • Handle: RePEc:ris:qmetal:2011_002
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    1. Bruce D. Grundy, "undated". "Option Prices and the Underlying Asset's Return Distribution (Reprint 012)," Rodney L. White Center for Financial Research Working Papers 11-91, Wharton School Rodney L. White Center for Financial Research.
    2. Jiang, George J. & Tian, Yisong S., 2010. "Forecasting Volatility Using Long Memory and Comovements: An Application to Option Valuation under SFAS 123R," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 45(2), pages 503-533, April.
    3. Tian, Yisong S., 2004. "Too much of a good incentive? The case of executive stock options," Journal of Banking & Finance, Elsevier, vol. 28(6), pages 1225-1245, June.
    4. Jennergren, L. Peter & Naslund, Bertil, 1996. "A class of options with stochastic lives and an extension of the Black-Scholes formula," European Journal of Operational Research, Elsevier, vol. 91(2), pages 229-234, June.
    5. Grundy, Bruce D, 1991. "Option Prices and the Underlying Asset's Return Distribution," Journal of Finance, American Finance Association, vol. 46(3), pages 1045-1069, July.
    6. León, Angel & Vaello-Sebastià, Antoni, 2010. "A simulation-based algorithm for American executive stock option valuation," Finance Research Letters, Elsevier, vol. 7(1), pages 14-23, March.
    7. Longstaff, Francis A & Schwartz, Eduardo S, 2001. "Valuing American Options by Simulation: A Simple Least-Squares Approach," University of California at Los Angeles, Anderson Graduate School of Management qt43n1k4jb, Anderson Graduate School of Management, UCLA.
    8. Kimura, Toshikazu, 2010. "Valuing executive stock options: A quadratic approximation," European Journal of Operational Research, Elsevier, vol. 207(3), pages 1368-1379, December.
    9. Lars Stentoft, 2004. "Assessing the Least Squares Monte-Carlo Approach to American Option Valuation," Review of Derivatives Research, Springer, vol. 7(2), pages 129-168, August.
    10. Longstaff, Francis A & Schwartz, Eduardo S, 2001. "Valuing American Options by Simulation: A Simple Least-Squares Approach," The Review of Financial Studies, Society for Financial Studies, vol. 14(1), pages 113-147.
    11. Hall, Brian J. & Murphy, Kevin J., 2002. "Stock options for undiversified executives," Journal of Accounting and Economics, Elsevier, vol. 33(1), pages 3-42, February.
    12. Bergstrom, A.R., 1984. "Continuous time stochastic models and issues of aggregation over time," Handbook of Econometrics, in: Z. Griliches† & M. D. Intriligator (ed.), Handbook of Econometrics, edition 1, volume 2, chapter 20, pages 1145-1212, Elsevier.
    13. Grundy, R.D., 1991. "Option Prices and the Underlying Asset's Return Distribution," Weiss Center Working Papers 11-91, Wharton School - Weiss Center for International Financial Research.
    14. Campbell, John Y. & Yogo, Motohiro, 2006. "Efficient tests of stock return predictability," Journal of Financial Economics, Elsevier, vol. 81(1), pages 27-60, July.
    15. Bettis, J. Carr & Bizjak, John M. & Lemmon, Michael L., 2005. "Exercise behavior, valuation, and the incentive effects of employee stock options," Journal of Financial Economics, Elsevier, vol. 76(2), pages 445-470, May.
    16. Carpenter, Jennifer N., 1998. "The exercise and valuation of executive stock options," Journal of Financial Economics, Elsevier, vol. 48(2), pages 127-158, May.
    17. Manuel Moreno & Javier Navas, 2003. "On the Robustness of Least-Squares Monte Carlo (LSM) for Pricing American Derivatives," Review of Derivatives Research, Springer, vol. 6(2), pages 107-128, May.
    18. Lo, Andrew W & Wang, Jiang, 1995. "Implementing Option Pricing Models When Asset Returns Are Predictable," Journal of Finance, American Finance Association, vol. 50(1), pages 87-129, March.
    19. Paschke, Raphael & Prokopczuk, Marcel, 2010. "Commodity derivatives valuation with autoregressive and moving average components in the price dynamics," Journal of Banking & Finance, Elsevier, vol. 34(11), pages 2742-2752, November.
    20. Hafner, Christian M. & Herwartz, Helmut, 2001. "Option pricing under linear autoregressive dynamics, heteroskedasticity, and conditional leptokurtosis," Journal of Empirical Finance, Elsevier, vol. 8(1), pages 1-34, March.
    21. Poterba, James M. & Summers, Lawrence H., 1988. "Mean reversion in stock prices : Evidence and Implications," Journal of Financial Economics, Elsevier, vol. 22(1), pages 27-59, October.
    22. Jonathan E. Ingersoll, Jr., 2006. "The Subjective and Objective Evaluation of Incentive Stock Options," The Journal of Business, University of Chicago Press, vol. 79(2), pages 453-488, March.
    23. Len, Angel & Vaello-Sebasti, Antoni, 2009. "American GARCH employee stock option valuation," Journal of Banking & Finance, Elsevier, vol. 33(6), pages 1129-1143, June.
    24. Philip Brown & Alex Szimayer, 2008. "Valuing executive stock options: performance hurdles, early exercise and stochastic volatility," Accounting and Finance, Accounting and Finance Association of Australia and New Zealand, vol. 48(3), pages 363-389, September.
    25. Lambert, Ra & Larcker, Df & Verrecchia, Re, 1991. "Portfolio Considerations In Valuing Executive-Compensation," Journal of Accounting Research, Wiley Blackwell, vol. 29(1), pages 129-149.
    26. Lars Stentoft, 2004. "Convergence of the Least Squares Monte Carlo Approach to American Option Valuation," Management Science, INFORMS, vol. 50(9), pages 1193-1203, September.
    27. Jin‐Chuan Duan, 1995. "The Garch Option Pricing Model," Mathematical Finance, Wiley Blackwell, vol. 5(1), pages 13-32, January.
    28. Nicholas Barberis, 2000. "Investing for the Long Run when Returns Are Predictable," Journal of Finance, American Finance Association, vol. 55(1), pages 225-264, February.
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    2. Lioui, Abraham & Poncet, Patrice, 2019. "Long horizon predictability: An asset allocation perspective," European Journal of Operational Research, Elsevier, vol. 278(3), pages 961-975.
    3. Abel Azze & Bernardo D'Auria & Eduardo Garc'ia-Portugu'es, 2022. "Optimal exercise of American options under time-dependent Ornstein-Uhlenbeck processes," Papers 2211.04095, arXiv.org, revised Dec 2023.
    4. Ioannis Kyriakou & Parastoo Mousavi & Jens Perch Nielsen & Michael Scholz, 2020. "Short-Term Exuberance and long-term stability: A simultaneous optimization of stock return predictions for short and long horizons," Graz Economics Papers 2020-20, University of Graz, Department of Economics.

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    More about this item

    Keywords

    Executive Stock Options; Risk Aversion; Undiversification; Predictability; FAS123R;
    All these keywords.

    JEL classification:

    • G11 - Financial Economics - - General Financial Markets - - - Portfolio Choice; Investment Decisions
    • G13 - Financial Economics - - General Financial Markets - - - Contingent Pricing; Futures Pricing
    • G17 - Financial Economics - - General Financial Markets - - - Financial Forecasting and Simulation
    • G35 - Financial Economics - - Corporate Finance and Governance - - - Payout Policy
    • M52 - Business Administration and Business Economics; Marketing; Accounting; Personnel Economics - - Personnel Economics - - - Compensation and Compensation Methods and Their Effects

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