Options Valuation in a High-frequency World

Document Type

Presentation

Presentation Date

10-2020

Abstract or Description

Presented at International Conference on Modern Management based on Big Data

Program

An alternative approach to the Black-Scholes-Merton formulation of option valuation is the entropy pricing theory. Entropy pricing applies notions of information theory to derive the theoretical value of options. I elaborate further on the maximum entropy formulation of option pricing using a generalized set of moment constraints. Higher order moments contain more information about the price density and characterize the shape of the underlying distribution. In a Monte Carlo study, I present entropies of heavy-tailed distributions and show that entropic call densities vary with constraints and become closer to each other as the order of moments increases. In an empirical analysis using high-frequency S&P 500 index options, I examine the impact of moment constraints on the accuracy of theoretical values. Simulation and empirical evidence suggest that the entropic pricing framework provides more accurate results for heavy-tailed, high-frequency data when higher order moment constraints are imposed.

Sponsorship/Conference/Institution

International Conference on Modern Management based on Big Data

Location

Virtual

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