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We study the martingale optimal transport problem with state-dependent trading frictions and develop a geometric and duality framework extending from the one time-step to the multi-marginal setting. Building on the left-monotone structure…

Optimization and Control · Mathematics 2025-10-14 Pratik Rai

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 establish sharp large deviation principles for cumulative rewards associated with a discrete-time renewal model, supposing that each renewal involves a broad-sense reward taking values in a real separable Banach space. The framework we…

Probability · Mathematics 2023-04-24 Marco Zamparo

We derive integral tests for the existence and absence of arbitrage in a financial market with one risky asset which is either modeled as stochastic exponential of an Ito process or a positive diffusion with Markov switching. In particular,…

Mathematical Finance · Quantitative Finance 2020-02-13 David Criens

We present a framework for hedging a portfolio of derivatives in the presence of market frictions such as transaction costs, market impact, liquidity constraints or risk limits using modern deep reinforcement machine learning methods. We…

Computational Finance · Quantitative Finance 2018-02-12 Hans Bühler , Lukas Gonon , Josef Teichmann , Ben Wood

This article prices OTC derivatives with either an exogenously determined initial margin profile or endogenously approximated initial margin. In the former case, margin valuation adjustment (MVA) is defined as the liability-side discounted…

Pricing of Securities · Quantitative Finance 2020-05-05 Wujiang Lou

This paper presents a stochastic model for discrete-time trading in financial markets where trading costs are given by convex cost functions and portfolios are constrained by convex sets. The model does not assume the existence of a cash…

Pricing of Securities · Quantitative Finance 2010-06-24 Teemu Pennanen

Differential ML (Huge and Savine 2020) is a technique for training neural networks to provide fast approximations to complex simulation-based models for derivatives pricing and risk management. It uses price sensitivities calculated through…

Pricing of Securities · Quantitative Finance 2026-04-23 Paul Glasserman , Siddharth Hemant Karmarkar

In this paper we solve the discrete time mean-variance hedging problem when asset returns follow a multivariate autoregressive hidden Markov model. Time dependent volatility and serial dependence are well established properties of financial…

Pricing of Securities · Quantitative Finance 2018-02-13 Massimo Caccia , Bruno Rémillard

Spread options are a fundamental class of derivative contract written on multiple assets, and are widely used in a range of financial markets. There is a long history of approximation methods for computing such products, but as yet there is…

Computational Finance · Quantitative Finance 2009-02-23 T. R. Hurd , Zhuowei Zhou

Suppose $\mu$ and $\nu$ are probability measures on $\mathbb R$ satisfying $\mu \leq_{cx} \nu$. Let $a$ and $b$ be convex functions on $\mathbb R$ with $a \geq b \geq 0$. We are interested in finding \[ \sup_{\mathcal M} \sup_{\tau}…

Mathematical Finance · Quantitative Finance 2025-03-20 David Hobson , Dominykas Norgilas

With model uncertainty characterized by a convex, possibly non-dominated set of probability measures, the agent minimizes the cost of hedging a path dependent contingent claim with given expected success ratio, in a discrete-time,…

Mathematical Finance · Quantitative Finance 2017-09-29 Erhan Bayraktar , Gu Wang

We consider the martingale optimal transport duality for c\`adl\`ag processes with given initial and terminal laws. Strong duality and existence of dual optimizers (robust semi-static superhedging strategies) are proved for a class of…

Probability · Mathematics 2019-04-10 Sebastian Herrmann , Florian Stebegg

We study martingale inequalities from an analytic point of view and show that a general martingale inequality can be reduced to a pair of deterministic inequalities in a small number of variables. More precisely, the optimal bound in the…

Probability · Mathematics 2014-10-21 Mathias Beiglböck , Marcel Nutz

This paper is devoted to a study of robust fundamental theorems of asset pricing in discrete time and finite horizon settings. Uncertainty is modelled by a (possibly uncountable) family of price processes on the same probability space. Our…

Mathematical Finance · Quantitative Finance 2024-04-04 Huy N. Chau

We propose a new class of finite element approximations to ideal compressible magnetohydrodynamic equations in smooth regime. Following variational approximations developed for fluid models in the last decade, our discretizations are built…

Numerical Analysis · Mathematics 2024-02-29 Valentin Carlier , Martin Campos-Pinto

The usual theory of asset pricing in finance assumes that the financial strategies, i.e. the quantity of risky assets to invest, are real-valued so that they are not integer-valued in general, see the Black and Scholes model for instance.…

Pricing of Securities · Quantitative Finance 2023-11-16 Dorsaf Cherif , Meriam El Mansour , Emmanuel Lepinette

This papers addresses the stock option pricing problem in a continuous time market model where there are two stochastic tradable assets, and one of them is selected as a num\'eraire. It is shown that the presence of arbitrarily small…

Pricing of Securities · Quantitative Finance 2014-10-01 Nikolai Dokuchaev

We consider the discretized version of a (continuous-time) two-factor model introduced by Benth and coauthors for the electricity markets. For this model, the underlying is the exponent of a sum of independent random variables. We provide…

Pricing of Securities · Quantitative Finance 2012-05-21 Stéphane Goutte , Nadia Oudjane , Francesco Russo

We present a new deep primal-dual backward stochastic differential equation framework based on stopping time iteration to solve optimal stopping problems. A novel loss function is proposed to learn the conditional expectation, which…

Computational Finance · Quantitative Finance 2024-09-12 Jiefei Yang , Guanglian Li