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Stochastic Processes in Pricing Financial Derivatives

A special issue of Entropy (ISSN 1099-4300). This special issue belongs to the section "Information Theory, Probability and Statistics".

Deadline for manuscript submissions: 31 December 2026 | Viewed by 1395

Editors


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Guest Editor
Systems Research Institute, Polish Academy of Sciences, Newelska 6, 01-447 Warsaw, Poland
Interests: computation and stochastic modelling in finance and insurance; financial mathematics; insurance mathematics; stochastic analysis; stochastic integration; probability; measure theory; fuzzy sets theory; statistics

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Guest Editor
Systems Research Institute, Polish Academy of Sciences, Newelska 6, 01-447 Warsaw, Poland
Interests: financial modelling; financial mathematics

Special Issue Information

Dear Colleagues,

Modeling financial instrument prices using stochastic processes has become a significant issue since the historic breakthrough made by Black and Scholes, who used geometric Brownian motion as a price model of the underlying financial instrument to value European options. Further research on financial markets resulted in the conclusion that the Black–Scholes model, although providing a convenient pricing formula, does not accurately reflect market reality. This fact led to the development of subsequent financial instrument models, among which exponential Lévy processes—generalizations of geometric Brownian motion—played a significant role. Lévy processes, in contrast to geometric Brownian motion, allow for the modelling of jumps in the price of the underlying asset, which makes stochastic modelling more realistic. Recently, even more complex stochastic processes, including those that do not fall within the class of semimartingales, have been employed as models for the derivative pricing problem. Moreover, some very sophisticated methods have also been developed to address pricing financial derivatives, such as the application of the Dupire formula.

Here, we collect new approaches to the broadly understood field of modeling and pricing financial derivatives. In particular, purely theoretical papers within the abovementioned field are welcome.

Dr. Piotr Nowak
Prof. Dr. Dariusz Gątarek
Guest Editors

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Keywords

  • financial derivatives pricing
  • Black–Scholes model
  • stochastic processes
  • Lévy processes
  • semimartingales
  • Dupire formula

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Published Papers (2 papers)

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Research

15 pages, 1195 KB  
Article
Analytic Approximation for Bachelier Option Prices and Applications
by Elisa Alòs and Òscar Burés
Entropy 2026, 28(6), 642; https://doi.org/10.3390/e28060642 - 6 Jun 2026
Viewed by 354
Abstract
It is well-known that, in the Bachelier model, when asset prices and volatilities are uncorrelated, the at-the-money implied volatility coincides with the fair value of the volatility swap. Using this identity as a starting point and applying classical Itô calculus and Taylor expansions, [...] Read more.
It is well-known that, in the Bachelier model, when asset prices and volatilities are uncorrelated, the at-the-money implied volatility coincides with the fair value of the volatility swap. Using this identity as a starting point and applying classical Itô calculus and Taylor expansions, we write the price for out-of the-money (OTM) and in-the-money (ITM) options as an expansion with respect to the moneyness, where the coefficients are related to the negative (non-integer) powers of the future mean volatility. As an a application, we use it as a control variate to reduce the variance of Monte Carlo option prices in the correlated case. Full article
(This article belongs to the Special Issue Stochastic Processes in Pricing Financial Derivatives)
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25 pages, 6261 KB  
Article
Stochastic and Statistical Analysis of Cnoidal, Snoidal, Dnoidal, Hyperbolic, Trigonometric and Exponential Wave Solutions of a Coupled Volatility Option-Pricing System
by L. M. Abdalgadir, Shabir Ahmad, Bakri Youniso and Khaled Aldwoah
Entropy 2026, 28(3), 353; https://doi.org/10.3390/e28030353 - 20 Mar 2026
Viewed by 475
Abstract
We investigate a stochastic coupled nonlinear Schrödinger (Manakov-type) system for option price and volatility wave fields within the Ivancevic adaptive-wave option-pricing paradigm, and derive exact wave families together with statistical diagnostics of the resulting dynamics. This system combines behavioral market effects with classical [...] Read more.
We investigate a stochastic coupled nonlinear Schrödinger (Manakov-type) system for option price and volatility wave fields within the Ivancevic adaptive-wave option-pricing paradigm, and derive exact wave families together with statistical diagnostics of the resulting dynamics. This system combines behavioral market effects with classical efficient-market dynamics and incorporates a controlled stochastic volatility component. Randomness in both the option price and volatility is incorporated via white noise, and a system of stochastic partial differential equations (PDEs) is developed that governs the joint evolution of option prices and stock price volatility. We derive advanced solutions of the proposed system using a newly created methodology. The obtained solutions are expressions of cnoidal, snoidal, dnoidal, hyperbolic, trigonometric, and exponential functions. The stochastic dynamical investigation, together with the statistical measures are presented. The autocorrelation function (ACF) of squared returns for the obtained analytical solutions is demonstrated to show distinct differences in second-order temporal dependence, while asymmetries in the temporal evolution of the fluctuations are depicted via leverage correlation (LC). The probability distribution function (PDF) dynamics of the soliton solutions illustrate prominent temporal variability and non-stationary statistical dynamics. Differences in dynamical coupling between the two components of the considered system are presented via phase velocity cross-correlation analysis and are supported by phase difference dynamics visualizations. The strength and structure of coupling between components are displayed via the amplitude cross-correlation function. Mean amplitude dynamics and variance as a function of noise intensity σ, provide a systematic influence of stochastic forcing on their energy and a quantitative measure of stochastic dispersion of soliton solutions. All the results are displayed in 3D and 2D graphs of the stochastics and statistical dynamics of the obtained solutions. Full article
(This article belongs to the Special Issue Stochastic Processes in Pricing Financial Derivatives)
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