Research on The Lookback Option Pricing of Disney Based on BSM Model
DOI:
https://doi.org/10.54691/bcpbm.v37i.3560Keywords:
Lookback option pricing, BSM Model, Disney company, Sensitivity analysis.Abstract
The lookback option is a path-dependent option that enables holders to use the most advantageous pricing to execute the underlying asset. This paper adopts the BMS model to price the lookback option and takes risk factors into consideration to calculate the value of an option contract in the BMS model. The main variables in the BMS model are risk-free rate, current spot price, strike price, volatility, and time to maturity. The results are reliable enough for investors to make future decisions. However, the BMS model still has a few drawbacks which can make the prices derived from real future prices. When predicting future prices, using the BMS model can help investors make better decisions. The lookback option allows holders to minimize their regrets and exercise the underlying asset at the most beneficial price.
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Leung, K.S. An analytic pricing formula for lookback options under stochastic volatility. Applied Mathematics Letters, 2013, 26(1): 145-149.
Fallah, S., Mehrdoust, F. On the existence and uniqueness of the solution to the double Heston model equation and valuing Lookback option. Journal of Computational and Applied Mathematics, 2019, 350: 412-422.
Park, H.S. Analytical binomial lookback options with double-exponential jumps. Journal of the Korean Statistical Society, 2009, 38(4): 397-404.
Cheuk, T.H.F., Vorst, T.C.F. Currency lookback options and observation frequency: A binomial approach. Journal of International Money and Finance, 1997, 16(2): 173-187.
Heynen, R. C., Kat, H. M. Lookback options with discrete and partial monitoring of the underlying price. Applied Mathematical Finance, 1995, 2(4): 273-284.
Buchen, P., Konstandatos, O. A new method of pricing lookback options. Mathematical Finance, 2005, 15: 245-259.
Chen Qisheng, Zhang Qian, Liu Chuan. The pricing and numerical analysis of lookback options for mixed fractional Brownian motion. Chaos, Solitons & Fractals, 2019, 128: 123-128.
Bender, C., Sottinen, T., Valkeila, E. Fractional Processes as Models in Stochastic Finance. Advanced Mathematical Methods for Finance, 2011, 75-103.
Ma Weijun, Liu Wei, Zhu Quanxin Zhu, Shi Kaibo. Dynamics of the Exponential Population Growth System with Mixed Fractional Brownian Motion. Complexity, 2021.
Azmoodeh, E., Valkeila, E. Spectral characterization of the quadratic variation of mixed Brownian–fractional Brownian motion. Stat Inference Stoch Process, 2013, 16: 97–112.
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