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The Generalized Gamma distribution as a useful RND under Heston's stochastic volatility model

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  • Ben Boukai

Abstract

Following Boukai (2021) we present the Generalized Gamma (GG) distribution as a possible RND for modeling European options prices under Heston's (1993) stochastic volatility (SV) model. This distribution is seen as especially useful in situations in which the spot's price follows a negatively skewed distribution and hence, Black-Scholes based (i.e. the log-normal distribution) modeling is largely inapt. We apply the GG distribution as RND to modeling current market option data on three large market-index ETFs, namely the SPY, IWM and QQQ as well as on the TLT (an ETF that tracks an index of long term US Treasury bonds). The current option chain of each of the three market-index ETFs shows of a pronounced skew of their volatility `smile' which indicates a likely distortion in the Black-Scholes modeling of such option data. Reflective of entirely different market expectations, this distortion appears not to exist in the TLT option data. We provide a thorough modeling of the available option data we have on each ETF (with the October 15, 2021 expiration) based on the GG distribution and compared it to the option pricing and RND modeling obtained directly from a well-calibrated Heston's (1993) SV model (both theoretically and empirically, using Monte-Carlo simulations of the spot's price). All three market-index ETFs exhibit negatively skewed distributions which are well-matched with those derived under the GG distribution as RND. The inadequacy of the Black-Scholes modeling in such instances which involve negatively skewed distribution is further illustrated by its impact on the hedging factor, delta, and the immediate implications to the retail trader. In contrast, for the TLT ETF, which exhibits no such distortion to the volatility `smile', the three pricing models (i.e. Heston's, Black-Scholes and Generalized Gamma) appear to yield similar results.

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  • Ben Boukai, 2021. "The Generalized Gamma distribution as a useful RND under Heston's stochastic volatility model," Papers 2108.07937, arXiv.org, revised Aug 2021.
    • Handle: RePEc:arx:papers:2108.07937
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    References listed on IDEAS

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    1. Robert Savickas, 2002. "A Simple Option‐Pricing Formula," The Financial Review, Eastern Finance Association, vol. 37(2), pages 207-226, May.
    2. Ben Boukai, 2020. "How Much Is Your Strangle Worth? On the Relative Value of the Strangle under the Black-Scholes Pricing Model," Applied Economics and Finance, Redfame publishing, vol. 7(4), pages 138-146, July.
    3. 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.
    4. Stein, Elias M & Stein, Jeremy C, 1991. "Stock Price Distributions with Stochastic Volatility: An Analytic Approach," The Review of Financial Studies, Society for Financial Studies, vol. 4(4), pages 727-752.
    5. Robert Savickas, 2005. "Evidence On Delta Hedging And Implied Volatilities For The Black‐Scholes, Gamma, And Weibull Option Pricing Models," Journal of Financial Research, Southern Finance Association;Southwestern Finance Association, vol. 28(2), pages 299-317, June.
    6. Robert C. Merton, 2005. "Theory of rational option pricing," World Scientific Book Chapters, in: Sudipto Bhattacharya & George M Constantinides (ed.), Theory Of Valuation, chapter 8, pages 229-288, World Scientific Publishing Co. Pte. Ltd..
    7. Lishang Jiang, 2005. "Mathematical Modeling and Methods of Option Pricing," World Scientific Books, World Scientific Publishing Co. Pte. Ltd., number 5855, February.
    8. 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.
    9. Kiche J & Oscar Ngesa & George Orwa, 2019. "On Generalized Gamma Distribution and Its Application to Survival Data," International Journal of Statistics and Probability, Canadian Center of Science and Education, vol. 8(5), pages 85-102, September.
    10. Gilles Pagès & Thibaut Montes & Vincent Lemaire, 2020. "Stationary Heston model: Calibration and Pricing of exotics using Product Recursive Quantization," Working Papers hal-02434232, HAL.
    11. Ben Boukai, 2020. "How much is your Strangle worth? On the relative value of the $\delta-$Symmetric Strangle under the Black-Scholes model," Papers 2003.03876, arXiv.org, revised May 2020.
    12. 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.
    13. Ben Boukai, 2021. "On the RND under Heston's stochastic volatility model," Papers 2101.03626, arXiv.org.
    14. Grith, Maria & Härdle, Wolfgang Karl & Schienle, Melanie, 2010. "Nonparametric estimation of risk-neutral densities," SFB 649 Discussion Papers 2010-021, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    15. Wiggins, James B., 1987. "Option values under stochastic volatility: Theory and empirical estimates," Journal of Financial Economics, Elsevier, vol. 19(2), pages 351-372, December.
    16. 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.
    17. Vincent Lemaire & Thibaut Montes & Gilles Pag`es, 2020. "Stationary Heston model: Calibration and Pricing of exotics using Product Recursive Quantization," Papers 2001.03101, arXiv.org, revised Jul 2020.
    18. Stephen Figlewski, 2018. "Risk-Neutral Densities: A Review," Annual Review of Financial Economics, Annual Reviews, vol. 10(1), pages 329-359, November.
    19. Jackwerth, Jens Carsten & Rubinstein, Mark, 1996. "Recovering Probability Distributions from Option Prices," Journal of Finance, American Finance Association, vol. 51(5), pages 1611-1632, December.
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