Additive Logistic Processes in Option Pricing
38 Pages Posted: 16 Sep 2020 Last revised: 20 Jul 2021
Date Written: August 3, 2020
In option pricing it is customary to first specify a stochastic underlying model and then extract valuation equations from it. Still, it is possible to reverse this paradigm: starting from an arbitrage-free option valuation formula, one could derive a family of risk-neutral probabilities and a corresponding risk-neutral underlying asset process. In this paper we start from two simple arbitrage-free valuation equations, inspired by the log-sum-exponential function and an $l^p$ vector norm. Such expressions lead respectively to logistic and Dagum (or ``log-skew-logistic'') risk-neutral distributions for the underlying security price. We proceed to exhibit supporting martingale processes of additive type for underlying securities having as time marginals two such distributions. By construction, these processes produce closed-form valuation equations which are even simpler than those of the Bachelier and Samuelson-Black-Scholes models.
Additive logistic processes provide parsimonious and simple option pricing models capturing various important stylized facts at the minimum price of a single market observable input.
Keywords: Logistic distribution, additive processes, derivative pricing, Dagum distribution, generalized-z distributions
JEL Classification: 91G20, 60H99
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