Application of Extended Normal Distribution in Option Price Sensitivities

Gangadhar Nayak, Subhranshu Sekhar Tripathy, Agbotiname Lucky Imoize () and Chun-Ta Li ()
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Gangadhar Nayak: Department of Mathematics and Humanities, Odisha University of Technology and Research, Bhubaneswar 751029, India
Subhranshu Sekhar Tripathy: School of Computer Engineering, KIIT Deemed to be University, Bhubaneswar 751024, India
Agbotiname Lucky Imoize: Department of Electrical and Electronics Engineering, Faculty of Engineering, University of Lagos, Akoka, Lagos 100213, Nigeria
Chun-Ta Li: Program of Artificial Intelligence and Information Security, Fu Jen Catholic University, New Taipei City 24205, Taiwan

Mathematics, 2024, vol. 12, issue 15, 1-18

Abstract: Empirical evidence indicates that asset returns adhere to an extended normal distribution characterized by excessive kurtosis and non-zero skewness. Consequently, option prices derived from this distribution diverge from those predicted by the Black–Scholes model. Despite the significance of option price sensitivities for risk management in investment portfolios, the existing literature lacks a thorough exploration of these sensitivities within the context of the extended normal distribution. This article addresses this research gap by deriving the Greeks for options based on the extended normal distribution. The Greeks under consideration include Vega, Delta, Theta, Gamma, Rho, Vanna, Charm, and Vera, all of which are crucial for informed financial decision-making. Furthermore, this study provides a detailed analysis of how these option price sensitivities vary with different levels of kurtosis, offering valuable insights for various market applications. This contribution not only enhances the theoretical understanding of option pricing under non-standard distributions but also presents practical implications for portfolio risk management.

Keywords: high-frequency trading; normal CDF; Q-function; option price; option Greeks (search for similar items in EconPapers)
JEL-codes: C (search for similar items in EconPapers)
Date: 2024
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