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Efficient option pricing on stocks paying discrete or path-dependent dividends with the stair tree

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  • Tian-Shyr Dai

Abstract

Pricing options on a stock that pays discrete dividends has not been satisfactorily settled because of the conflicting demands of computational tractability and realistic modelling of the stock price process. Many papers assume that the stock price minus the present value of future dividends or the stock price plus the forward value of future dividends follows a lognormal diffusion process; however, these assumptions might produce unreasonable prices for some exotic options and American options. It is more realistic to assume that the stock price decreases by the amount of the dividend payout at the ex-dividend date and follows a lognormal diffusion process between adjacent ex-dividend dates, but analytical pricing formulas and efficient numerical methods are hard to develop. This paper introduces a new tree, the stair tree, that faithfully implements the aforementioned dividend model without approximations. The stair tree uses extra nodes only when it needs to simulate the price jumps due to dividend payouts and return to a more economical, simple structure at all other times. Thus it is simple to construct, easy to understand, and efficient. Numerous numerical calculations confirm the stair tree's superior performance to existing methods in terms of accuracy, speed, and/or generality. Besides, the stair tree can be extended to more general cases when future dividends are completely determined by past stock prices and dividends, making the stair tree able to model sophisticated dividend processes.

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  • Tian-Shyr Dai, 2009. "Efficient option pricing on stocks paying discrete or path-dependent dividends with the stair tree," Quantitative Finance, Taylor & Francis Journals, vol. 9(7), pages 827-838.
  • Handle: RePEc:taf:quantf:v:9:y:2009:i:7:p:827-838
    DOI: 10.1080/14697680902814217
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    References listed on IDEAS

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    2. Wang, Chuan-Ju & Dai, Tian-Shyr & Lyuu, Yuh-Dauh, 2014. "Evaluating corporate bonds with complicated liability structures and bond provisions," European Journal of Operational Research, Elsevier, vol. 237(2), pages 749-757.
    3. Tian-Shyr Dai & Chun-Yuan Chiu, 2013. "Pricing barrier stock options with discrete dividends by approximating analytical formulae," Quantitative Finance, Taylor & Francis Journals, vol. 14(8), pages 1367-1382, October.
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    5. Ma, Jingtang & Fan, Jiacheng, 2016. "Convergence rates of recombining trees for pricing options on stocks under GBM and regime-switching models with known cash dividends," The North American Journal of Economics and Finance, Elsevier, vol. 37(C), pages 128-147.
    6. Paolo Angelis & Roberto Marchis & Antonio L. Martire & Emilio Russo, 2022. "A flexible lattice framework for valuing options on assets paying discrete dividends and variable annuities embedding GMWB riders," Decisions in Economics and Finance, Springer;Associazione per la Matematica, vol. 45(1), pages 415-446, June.
    7. Tian‐Shyr Dai & Chen‐Chiang Fan & Liang‐Chih Liu & Chuan‐Ju Wang & Jr‐Yan Wang, 2022. "A stochastic‐volatility equity‐price tree for pricing convertible bonds with endogenous firm values and default risks determined by the first‐passage default model," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 42(12), pages 2103-2134, December.

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