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In this paper, we propose a probabilistic optimization method, named probabilistic incremental proximal gradient (PIPG) method, by developing a probabilistic interpretation of the incremental proximal gradient algorithm. We explicitly model…

Optimization and Control · Mathematics 2019-06-20 Ömer Deniz Akyildiz , Émilie Chouzenoux , Víctor Elvira , Joaquín Míguez

One of the most fundamental questions in quantitative finance is the existence of continuous-time diffusion models that fit market prices of a given set of options. Traditionally, one employs a mix of intuition, theoretical and empirical…

Computational Finance · Quantitative Finance 2023-10-09 Nelson Vadori

We investigate methods for pricing American options under the variance gamma model. The variance gamma process is a pure jump process which is constructed by replacing the calendar time by the gamma time in a Brownian motion with drift,…

Computational Finance · Quantitative Finance 2022-07-04 Weilong Fu , Ali Hirsa

We present a methodology to price options and portfolios of options on a gate-based quantum computer using amplitude estimation, an algorithm which provides a quadratic speedup compared to classical Monte Carlo methods. The options that we…

Stochastic resetting is a rapidly developing topic in the field of stochastic processes and their applications. It denotes the occasional reset of a diffusing particle to its starting point and effects, inter alia, optimal first-passage…

Statistical Mechanics · Physics 2023-05-25 C. Di Bello , A. V. Chechkin , A. K. Hartmann , Z. Palmowski , R. Metzler

The proposed model modifies option pricing formulas for the basic case of log-normal probability distribution providing correspondence to formulated criteria of efficiency and completeness. The model is self-calibrating by historic…

Pricing of Securities · Quantitative Finance 2008-12-02 Pavel Levin

The aim of this chapter is to show how option prices in jump-diffusion models can be computed using meshless methods based on Radial Basis Function (RBF) interpolation. The RBF technique is demonstrated by solving the partial…

Computational Finance · Quantitative Finance 2011-10-26 Ron T. L. Chan , Simon Hubbert

Financial derivative pricing is a significant challenge in finance, involving the valuation of instruments like options based on underlying assets. While some cases have simple solutions, many require complex classical computational methods…

Computational Finance · Quantitative Finance 2025-05-15 Robert Scriba , Yuying Li , Jingbo B Wang

In this paper, we study a pricing problem of the multiple reset put option, which allows the holder to reset several times a current strike price to obtain an at-the-money European put option. We formulate the pricing problem as a multiple…

Pricing of Securities · Quantitative Finance 2021-09-21 Nazym Azimbayev , Yerkin Kitapbayev

The paper studies sub and super-replication price bounds for contingent claims defined on general trajectory based market models. No prior probabilistic or topological assumptions are placed on the trajectory space, trading is assumed to…

Mathematical Finance · Quantitative Finance 2018-02-22 Ivan Degano , Sebastian Ferrando , Alfredo Gonzalez

Computation of moments of transformed random variables is a problem appearing in many engineering applications. The current methods for moment transformation are mostly based on the classical quadrature rules which cannot account for the…

Methodology · Statistics 2017-01-06 Jakub Prüher , Ondřej Straka

This paper develops a probabilistic numerical method for solution of partial differential equations (PDEs) and studies application of that method to PDE-constrained inverse problems. This approach enables the solution of challenging inverse…

Methodology · Statistics 2017-07-12 Jon Cockayne , Chris Oates , Tim Sullivan , Mark Girolami

In this paper, we consider option pricing in a framework of the fractional Heston-type model with $H>1/2$. As it is impossible to obtain an explicit formula for the expectation $\mathbb E f(S_T)$ in this case, where $S_T$ is the asset price…

Probability · Mathematics 2019-07-04 Yuliya Mishura , Anton Yurchenko-Tytarenko

We introduce a novel signature approach for pricing and hedging path-dependent options with instantaneous and permanent market impact under a mean-quadratic variation criterion. Leveraging the expressive power of signatures, we recast an…

Portfolio Management · Quantitative Finance 2025-12-01 Eduardo Abi Jaber , Donatien Hainaut , Edouard Motte

We price European and American exchange options where the underlying asset prices are modelled using a Merton (1976) jump-diffusion with a common Heston (1993) stochastic volatility process. Pricing is performed under an equivalent…

Mathematical Finance · Quantitative Finance 2020-02-25 Len Patrick Dominic M. Garces , Gerald H. L. Cheang

This paper examines the joint problem of detection and identification of a sudden and unobservable change in the probability distribution function (pdf) of a sequence of independent and identically distributed (i.i.d.) random variables to…

Information Theory · Computer Science 2009-04-16 Savas Dayanik , Christian Goulding , H. Vincent Poor

In this work, we present the methods necessary to price an important set of derivatives on a quantum device while offering an advantage over existing classical methods. The methods developed here, in conjunction with ~\cite{GumaroS2026},…

Quantum Physics · Physics 2026-05-29 Gumaro Rendon , Stepan Smid , Sarvagya Upadhyay

A popular approach to nonparametric option pricing is the Minimum Cross Entropy (MCE) method based on minimization of the relative Kullback-Leibler entropy of the price density distribution and a given reference density, with observable…

Statistical Mechanics · Physics 2007-05-23 Igor Halperin

There exists an entire family of universal PDFs of the magnetization mode of the three dimensional Ising model parameterized by $\zeta = \lim_{L,\xi_{\infty}}L/\xi_{\infty}$ which is the ratio of the system size $L$ to the bulk correlation…

Statistical Mechanics · Physics 2025-12-15 Sankarshan Sahu

We study higher statistical moments of Distortion for randomized social choice in a metric implicit utilitarian model. The Distortion of a social choice mechanism is the expected approximation factor with respect to the optimal utilitarian…

Computer Science and Game Theory · Computer Science 2020-04-29 Brandon Fain , William Fan , Kamesh Munagala