IDEAS home Printed from https://ideas.repec.org/p/iik/wpaper/294.html
   My bibliography  Save this paper

A simpler algorithm to price American Lookback options in a discrete stochastic volatility model

Author

Listed:
  • L. Ramprasath

    (Indian Institute of Management Kozhikode)

Abstract

This article develops an efficient pricing algorithm for American lookback options on a binomial lattice with stochastic volatility. This is achieved by combining the structure of this lattice together with the fact that one can price lookbacks on a standard binomial lattice without having to store the path variables. We apply this algorithm to study the efficiency of fractional lookback contracts, which are used as a benchmark for designing equity indexed annuities, and illustrate the impact of volatility persistence on their prices. This algorithm also extends the usefulness of the stochastic volatility model proposed by Aingworth, Das and Motwani (2006) by enabling the pricing of lookback options on their lattice.

Suggested Citation

  • L. Ramprasath, 2018. "A simpler algorithm to price American Lookback options in a discrete stochastic volatility model," Working papers 294, Indian Institute of Management Kozhikode.
    • Handle: RePEc:iik:wpaper:294
    as

    Download full text from publisher

    File URL: https://iimk.ac.in/websiteadmin/FacultyPublications/Working%20Papers/2983294%20August.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Tze Leung Lai & Tiong Wee Lim, 2004. "Exercise Regions And Efficient Valuation Of American Lookback Options," Mathematical Finance, Wiley Blackwell, vol. 14(2), pages 249-269, April.
    2. Heston, Steven L, 1993. "A Closed-Form Solution for Options with Stochastic Volatility with Applications to Bond and Currency Options," Review of Financial Studies, Society for Financial Studies, vol. 6(2), pages 327-343.
    3. Donald Aingworth & Sanjiv Das & Rajeev Motwani, 2006. "A simple approach for pricing equity options with Markov switching state variables," Quantitative Finance, Taylor & Francis Journals, vol. 6(2), pages 95-105.
    4. Hans Gerber & Elias Shiu, 2003. "Pricing Lookback Options and Dynamic Guarantees," North American Actuarial Journal, Taylor & Francis Journals, vol. 7(1), pages 48-66.
    5. Cheuk, Terry H. F. & Vorst, Ton C. F., 1997. "Currency lookback options and observation frequency: A binomial approach," Journal of International Money and Finance, Elsevier, vol. 16(2), pages 173-187, April.
    6. 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.
    7. Massimo Costabile & Arturo Leccadito & Ivar Massabó & Emilio Russo, 2014. "A reduced lattice model for option pricing under regime-switching," Review of Quantitative Finance and Accounting, Springer, vol. 42(4), pages 667-690, May.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Emilio Russo, 2020. "A Discrete-Time Approach to Evaluate Path-Dependent Derivatives in a Regime-Switching Risk Model," Risks, MDPI, vol. 8(1), pages 1-22, January.
    2. Lim, Terence & Lo, Andrew W. & Merton, Robert C. & Scholes, Myron S., 2006. "The Derivatives Sourcebook," Foundations and Trends(R) in Finance, now publishers, vol. 1(5–6), pages 365-572, April.
    3. Cheng Few Lee & Yibing Chen & John Lee, 2020. "Alternative Methods to Derive Option Pricing Models: Review and Comparison," World Scientific Book Chapters, in: Cheng Few Lee & John C Lee (ed.), HANDBOOK OF FINANCIAL ECONOMETRICS, MATHEMATICS, STATISTICS, AND MACHINE LEARNING, chapter 102, pages 3573-3617, World Scientific Publishing Co. Pte. Ltd..
    4. Chourdakis, Kyriakos & Dendramis, Yiannis & Tzavalis, Elias, 2014. "Are regime-shift sources of risk priced in the market?," Journal of Empirical Finance, Elsevier, vol. 28(C), pages 151-170.
    5. Lo, C.C. & Nguyen, D. & Skindilias, K., 2017. "A Unified Tree approach for options pricing under stochastic volatility models," Finance Research Letters, Elsevier, vol. 20(C), pages 260-268.
    6. Song-Ping Zhu & Xin-Jiang He, 2018. "A hybrid computational approach for option pricing," International Journal of Financial Engineering (IJFE), World Scientific Publishing Co. Pte. Ltd., vol. 5(03), pages 1-16, September.
    7. Jobst, Andreas A., 2014. "Measuring systemic risk-adjusted liquidity (SRL)—A model approach," Journal of Banking & Finance, Elsevier, vol. 45(C), pages 270-287.
    8. Yongxin Yang & Yu Zheng & Timothy M. Hospedales, 2016. "Gated Neural Networks for Option Pricing: Rationality by Design," Papers 1609.07472, arXiv.org, revised Mar 2020.
    9. Peter Christoffersen & Ruslan Goyenko & Kris Jacobs & Mehdi Karoui, 2018. "Illiquidity Premia in the Equity Options Market," Review of Financial Studies, Society for Financial Studies, vol. 31(3), pages 811-851.
    10. Hentati-Kaffel, R. & Prigent, J.-L., 2016. "Optimal positioning in financial derivatives under mixture distributions," Economic Modelling, Elsevier, vol. 52(PA), pages 115-124.
    11. Seiji Harikae & James S. Dyer & Tianyang Wang, 2021. "Valuing Real Options in the Volatile Real World," Production and Operations Management, Production and Operations Management Society, vol. 30(1), pages 171-189, January.
    12. Dong-Mei Zhu & Jiejun Lu & Wai-Ki Ching & Tak-Kuen Siu, 2019. "Option Pricing Under a Stochastic Interest Rate and Volatility Model with Hidden Markovian Regime-Switching," Computational Economics, Springer;Society for Computational Economics, vol. 53(2), pages 555-586, February.
    13. Baeho Kim & Da‐Hea Kim & Haehean Park, 2020. "Informed options trading on the implied volatility surface: A cross‐sectional approach," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 40(5), pages 776-803, May.
    14. Steven L. Heston & Alberto G. Rossi, 2017. "A Spanning Series Approach to Options," The Review of Asset Pricing Studies, Society for Financial Studies, vol. 7(1), pages 2-42.
    15. Lin, Zih-Ying & Chang, Chuang-Chang & Wang, Yaw-Huei, 2018. "The impacts of asymmetric information and short sales on the illiquidity risk premium in the stock option market," Journal of Banking & Finance, Elsevier, vol. 94(C), pages 152-165.
    16. Jianhui Li & Sebastian A. Gehricke & Jin E. Zhang, 2019. "How do US options traders “smirk” on China? Evidence from FXI options," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 39(11), pages 1450-1470, November.
    17. Chatterjee, Somnath & Jobst, Andreas, 2019. "Market-implied systemic risk and shadow capital adequacy," Bank of England working papers 823, Bank of England.
    18. Gianluca Frasso & Jonathan Jaeger & Philippe Lambert, 2016. "Parameter estimation and inference in dynamic systems described by linear partial differential equations," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 100(3), pages 259-287, July.
    19. Duy Nguyen, 2018. "A hybrid Markov chain-tree valuation framework for stochastic volatility jump diffusion models," International Journal of Financial Engineering (IJFE), World Scientific Publishing Co. Pte. Ltd., vol. 5(04), pages 1-30, December.
    20. Cosma, Antonio & Galluccio, Stefano & Pederzoli, Paola & Scaillet, Olivier, 2020. "Early Exercise Decision in American Options with Dividends, Stochastic Volatility, and Jumps," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 55(1), pages 331-356, February.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:iik:wpaper:294. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sudheesh Kumar (email available below). General contact details of provider: https://edirc.repec.org/data/iikmmin.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.