Additive logistic processes in option pricing

Peter Carr, Lorenzo Torricelli

Research output: Contribution to journalArticlepeer-review


In option pricing, it is customary to first specify a stochastic underlying model and then extract valuation equations from it. However, 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 ℓp 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 stylised facts at the minimum price of a single market observable input.

Original languageEnglish (US)
Pages (from-to)689-724
Number of pages36
JournalFinance and Stochastics
Issue number4
StatePublished - Oct 2021


  • Additive processes
  • Dagum distribution
  • Derivative pricing
  • Generalised z-distributions
  • Logistic distribution

ASJC Scopus subject areas

  • Statistics and Probability
  • Finance
  • Statistics, Probability and Uncertainty


Dive into the research topics of 'Additive logistic processes in option pricing'. Together they form a unique fingerprint.

Cite this