Pricing European Call Options with Visualization Based on the Binomial Model, Monte-Carlo Simulation, and Classical Black-Scholes Model
DOI:
https://doi.org/10.54097/85byzq20Keywords:
European call options; option pricing; binomial model; Black-Scholes model, Monte-Carlo simulation.Abstract
After the emergence of financial derivatives, pricing has been focused by a considerable number of mathematicians. With stochastic analysis and some classic probability theories, many new pricing formulas appeared in the quantitative finance field. The improvement of pricing methods of different financial securities has essentially made prices more precise and more strict, thus greatly promoting the development of modern financial markets. In this research paper, the author reviewed three significant option pricing models in mathematical finance, which are the binomial model, classical Black-Scholes model, and Monte-Carlo simulation, and applied these three models to give the price of European options. Based on the results of these three models, the author conducted some visualization work and statistical work to compare the differences of the models. Furthermore, in order to determine the most suitable model in this case, the machine learning technique is applied to classify the price data by analyzing the confusion matrices in each model.
Downloads
References
Turner Evan. The Black-Scholes model and extensions. University of Chicago, 2010.
Cox John C, et al. Option pricing: A simplified approach. Journal of financial Economics, 1979, 7(3): 229-263.
Bates David S. Empirical option pricing: A retrospection. Journal of Econometrics, 2003, 116(1-2): 387-404.
Hull John. Options, futures, and other derivative securities. Englewood Cliffs, NJ: Prentice Hall, 1993.
Merton, Robert C. Theory of rational option pricing. The Bell Journal of economics and management science, 1973, 141-183.
Jarrow Robert A, George S. Forward contracts and futures contracts. Journal of Financial Economics, 1981, 9(4): 373-382.
Bessembinder Hendrik. Forward contracts and firm value: Investment incentive and contracting effects. Journal of Financial and quantitative Analysis, 1991, 26(4): 519-532.
Yahoo finance, Nasdaq, Inc. (NDAQ), 2023, https://finance.yahoo.com/quote/NDAQ/options/.
Bansal Ravi, Salim Viswanathan. No arbitrage and arbitrage pricing: A new approach. The Journal of Finance, 1993, 48(4): 1231-1262.
Carr Peter, Dilip B. Madan. A note on sufficient conditions for no arbitrage. Finance Research Letters, 2005, 2(3): 125-130.
Rogers Leonard, Christopher Gordon. Equivalent martingale measures and no-arbitrage. Stochastics: An International Journal of Probability and Stochastic Processes, 1994, 51(1-2): 41-49.
Jabbour George M, Yi Kang Liu. Option pricing and Monte Carlo simulations. Journal of Business & Economics Research (JBER), 2005, 3(9).
Kumar Arya. A Study on Risk Hedging Strategy: Efficacy Of Option Greeks. Abhinav National Monthly Refereed Journal of Research in Commerce & Management, 2018, 7(4): 77-85.
Li Minqiang. Closed-form approximations for spread option prices and Greeks. Munich Personal RePEc Archive, 2000.
Jonathan Cheung-Wai Chan, Desire Paelinckx. Evaluation of random forest and adaboost tree-based ensemble classification and spectral band selection for ecotope mapping using airborne hyperspectral imagery. Remote Sensing of Environment, 2008, 112(6): 2999–3011.
Pushpa Singh, et al. Diagnosing of disease using machine learning. Machine learning and the internet of medical things in healthcare. Academic Press, 2021, 89–111.
Apostolos Ampountolas, Titus Nyarko Nde, Paresh Date, et al. A machine learning approach for micro-credit scoring. Risks, 2021, 9(3):50.
Tharwat Alaa. Classification assessment methods. Applied computing and informatics, 2020, 17(1): 168-192.
Powers David MW. Evaluation: from precision, recall and F-measure to ROC, informedness, markedness and correlation. Flinders University, 2020.
Sasaki Yutaka. The truth of the F-measure. Teach tutor mater, 2007, 1(5): 1-5.
Downloads
Published
Issue
Section
License
Copyright (c) 2024 Highlights in Science, Engineering and Technology

This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.







