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Statistical Optimization of Option Pricing Factors: Application of Taguchi's DOE
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Author(s): Amir Ahmad dar (Lovely Professional University, India), Garima Sharma (Manav Rachna International Institute of Research and Studies, India), Shavej Ali Siddiqui (Khwaja Moinuddin Chishti Language University, India), Olayan Albalawi (University of Tabuk, Saudi Arabia), Bilal Ahmad Chat (Islamic University of Science and Technology, India)and Princy Yadav (Lovely Professional University, India)
Copyright: 2025
Pages: 18
Source title:
Data Analytics and AI for Quantitative Risk Assessment and Financial Computation
Source Author(s)/Editor(s): Mohammad Gouse Galety (Samarkand International University of Technology, Uzbekistan), Jimbo Henri Claver (Samarkand Interntional University of Technology, Uzbekistan), A. V. Sriharsha (Mohan Babu University, India), Narasimha Rao Vajjhala (University of New York Tirana, Tirana, Albania)and Arul Kumar Natarajan (Samarkand International University of Technology, Uzbekistan)
DOI: 10.4018/979-8-3693-6215-0.ch014
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Abstract
Options are a highly versatile trading tool renowned for mitigating downside risk while offering unlimited upside potential. The effectiveness and profitability of trading options hinge on selecting the right option at the appropriate price. Traditionally, the Binomial option pricing model (BOPM) is employed to estimate the fair value of options. This study delves into the impact of factors such as underlying asset price, strike price, volatility, and period (with a constant interest rate) on put option values. Leveraging Taguchi's design of experiment methodology, the research aims to optimize these factors for option valuation, marking the first instance of such optimization using Taguchi's method. Through a design of experiment (DOE), analysis of variance (ANOVA), regression analysis, and analysis of mean (ANOM), the study examines the effects of input factors, employing MINITAB 18 software for analysis.
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