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The multidimensional Uncertain Volatility Model leads to robust option pricing problems under joint volatility and correlation uncertainty. Their numerical resolution quickly becomes challenging because the associated stochastic control…

Computational Finance · Quantitative Finance 2026-05-11 Lokman A Abbas-Turki , Jean-François Chassagneux , Jean-Philippe Lemor , Grégoire Loeper , Simon Sananes

We discuss two numerical methods, based on a path integral approach described in a previous paper (I), for solving the stochastic equations underlying the financial markets: the Monte Carlo approach, and the Green function deterministic…

Statistical Mechanics · Physics 2008-12-10 Marco Rosa-Clot , Stefano Taddei

We propose a hybrid quantum-classical algorithm, originated from quantum chemistry, to price European and Asian options in the Black-Scholes model. Our approach is based on the equivalence between the pricing partial differential equation…

Computational Finance · Quantitative Finance 2021-02-08 Filipe Fontanela , Antoine Jacquier , Mugad Oumgari

We show that prices and shortfall risks of game (Israeli) barrier options in a sequence of binomial approximations of the Black--Scholes (BS) market converge to the corresponding quantities for similar game barrier options in the BS market…

Pricing of Securities · Quantitative Finance 2009-07-24 Yan Dolinsky , Yuri Kifer

In this paper a time-fractional Black-Scholes model (TFBSM) is considered to study the price change of the underlying fractal transmission system. We develop and analyze a numerical method to solve the TFBSM governing European options. The…

Numerical Analysis · Mathematics 2022-07-20 Anshima Singh , Sunil Kumar

We examine the possibility of incorporating information or views of market movements during the holding period of a portfolio, in the hedging of European options with respect to the underlying. Given a fixed holding period interval, we…

Mathematical Finance · Quantitative Finance 2015-10-23 Antoine E. Zambelli

The Black Box Variational Inference (Ranganath et al. (2014)) algorithm provides a universal method for Variational Inference, but taking advantage of special properties of the approximation family or of the target can improve the…

Computation · Statistics 2019-06-18 Alexander Immer , Guillaume P. Dehaene

Bayesian Optimization (BO) is a method for globally optimizing black-box functions. While BO has been successfully applied to many scenarios, developing effective BO algorithms that scale to functions with high-dimensional domains is still…

Machine Learning · Computer Science 2024-02-13 Yihang Shen , Carl Kingsford

Pricing of exotic financial derivatives, such as Asian and multi-asset American basket options, poses significant challenges for standard numerical methods such as binomial trees or Monte Carlo methods. While the former often scales…

Computational Finance · Quantitative Finance 2025-05-26 Maarten van Damme , Rishi Sreedhar , Martin Ganahl

There are no known exact formulas for the valuation of a number of exotic options, and this is particularly true for options under discrete monitoring and for American style options. Therefore, one usually recourses to a Monte Carlo…

Computational Finance · Quantitative Finance 2008-12-10 JC Ndogmo

Control variates are variance reduction tools for Monte Carlo estimators. They can provide significant variance reduction, but usually require a large number of samples, which can be prohibitive when sampling or evaluating the integrand is…

Methodology · Statistics 2023-06-08 Zhuo Sun , Alessandro Barp , François-Xavier Briol

In this paper, we discuss a simple yet robust PDE method for evaluating path-dependent Asian-style options using the non-oscillatory forward-in-time second-order MPDATA finite-difference scheme. The valuation methodology involves casting…

Computational Finance · Quantitative Finance 2025-06-02 Paweł Magnuszewski , Sylwester Arabas

This research addresses accurate option pricing by employing models beyond the traditional Black-Scholes framework. While Black-Scholes provides a closed-form solution, it is limited by assumptions of constant volatility, no dividends, and…

Computational Finance · Quantitative Finance 2026-04-08 Karmanpartap Singh Sidhu , Pranshi Saxena

The purpose of this paper is to analyze and compute the early exercise boundary for a class of nonlinear Black--Scholes equations with a nonlinear volatility which can be a function of the second derivative of the option price itself. A…

Computational Finance · Quantitative Finance 2008-12-10 Daniel Sevcovic

In this paper we derive an effective equation for derivative pricing which accounts for the presence of virtual arbitrage opportunities and their elimination by the market. We model the arbitrage return by a stochastic process and find an…

Statistical Mechanics · Physics 2008-12-02 Kirill Ilinski , Alexander Stepanenko

In this work, we present a quantum algorithm designed to solve the differential equation used in the pricing of Asian options, in the framework of the Black-Scholes model. Our approach modifies an existing quantum pre-conditioning method…

Quantum Physics · Physics 2025-05-09 Gumaro Rendon , Rutuja Kshirsagar , Quoc Hoan Tran

This thesis provides an overview of the recent advances in reinforcement learning in pricing and hedging financial instruments, with a primary focus on a detailed explanation of the Q-Learning Black Scholes approach, introduced by Halperin…

Computational Finance · Quantitative Finance 2023-10-09 Zoran Stoiljkovic

This paper presents a novel way to predict options price for one day in advance, utilizing the method of Quasi-Reversibility for solving the Black-Scholes equation. The Black-Scholes equation solved forwards in time with Tikhonov…

Analysis of PDEs · Mathematics 2022-03-21 Mikhail V. Klibanov , Kirill V. Golubnichiy , Andrey V. Nikitin

In this paper we present two parallel Monte Carlo based algorithms for pricing multi--dimensional Bermudan/American options. First approach relies on computation of the optimal exercise boundary while the second relies on classification of…

Distributed, Parallel, and Cluster Computing · Computer Science 2014-02-18 Mireille Bossy , Françoise Baude , Viet Dung Doan , Abhijeet Gaikwad , Ian Stokes-Rees

We present a differential machine learning method for zero-days-to-expiry (0DTE) options under a stochastic-volatility jump-diffusion model. To handle the ultra-short-maturity regime, we express the option price in Black-Scholes form with a…

Computational Finance · Quantitative Finance 2026-04-10 Takayuki Sakuma