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We present a parallel algorithm that computes the ask and bid prices of an American option when proportional transaction costs apply to the trading of the underlying asset. The algorithm computes the prices on recombining binomial trees,…

Distributed, Parallel, and Cluster Computing · Computer Science 2011-10-12 Nan Zhang , Alet Roux , Tomasz Zastawniak

In this work, we propose an algorithm to price American options by directly solving the dual minimization problem introduced by Rogers. Our approach relies on approximating the set of uniformly square integrable martingales by a finite…

Probability · Mathematics 2016-04-13 Jérôme Lelong

Markov decision models (MDM) used in practical applications are most often less complex than the underlying `true' MDM. The reduction of model complexity is performed for several reasons. However, it is obviously of interest to know what…

Optimization and Control · Mathematics 2019-09-18 Patrick Kern , Axel Simroth , Henryk Zähle

The paper is devoted to modeling optimal exercise strategies of the behavior of investors and issuers working with convertible bonds. This implies solution of the problems of stock price modeling, payoff computation and min-max…

Pricing of Securities · Quantitative Finance 2008-12-02 Kateryna Mishchenko , Volodymyr Mishchenko , Anatoliy Malyarenko

For a class of tempered fractional terminal value problems of the Caputo type, we study the existence and uniqueness of the solution, analyse the continuous dependence on the given data and using a shooting method, we present and discuss…

Numerical Analysis · Mathematics 2017-05-12 Luisa Morgado , Magda Rebelo

Models to price long term loans in the securities lending business are developed. These longer horizon deals can be viewed as contracts with optionality embedded in them. This insight leads to the usage of established methods from…

Pricing of Securities · Quantitative Finance 2022-03-29 Ravi Kashyap

This article is a sequel to [A.H.M.P]. In [A.H.M.P], we develop an explicit formula for pricing European options when the underlying stock price follows a non-linear stochastic delay equation with fixed delays in the drift and diffusion…

Probability · Mathematics 2008-12-02 Mercedes Arriojas , Yaozhong Hu , Salah-Eldin Mohammed , Gyula Pap

The general method is proposed for constructing a family of martingale measures for a wide class of evolution of risky assets. The sufficient conditions are formulated for the evolution of risky assets under which the family of equivalent…

Pricing of Securities · Quantitative Finance 2020-10-27 N. S. Gonchar

In this article, we combine replication pricing with expectation pricing for derivative trades that are partially collateralized by cash. The derivatives are replicated by underlying assets and cash, using repurchasing agreement (repo) and…

Pricing of Securities · Quantitative Finance 2013-02-05 Lixin Wu

In this note, we develop stock option price approximations for a model which takes both the risk o default and the stochastic volatility into account. We also let the intensity of defaults be influenced by the volatility. We show that it…

Computational Engineering, Finance, and Science · Computer Science 2007-12-21 Erhan Bayraktar

How to compute (super) hedging costs in rather general fi- nancial market models with transaction costs in discrete-time ? Despite the huge literature on this topic, most of results are characterizations of the super-hedging prices while it…

Probability · Mathematics 2024-05-13 Emmanuel Lepinette , Duc Thinh Vu

We study an algorithm which has been proposed by Chinesta et al. to solve high-dimensional partial differential equations. The idea is to represent the solution as a sum of tensor products and to compute iteratively the terms of this sum.…

Analysis of PDEs · Mathematics 2013-09-18 José Arturo Infante Acevedo , Tony Lelievre

We consider the numerical approximation of the quantile hedging price in a non-linear market. In a Markovian framework, we propose a numerical method based on a Piecewise Constant Policy Timestepping (PCPT) scheme coupled with a monotone…

Computational Finance · Quantitative Finance 2021-02-17 Cyril Bénézet , Jean-François Chassagneux , Christoph Reisinger

G-expectation, as a sublinear expectation, provides a powerful framework for modeling uncertainty in financial markets. Motivated by the need for robust valuation under model uncertainty, this work develops a unified risk-neutral valuation…

Computational Engineering, Finance, and Science · Computer Science 2026-03-25 Ziting Pei , Xingye Yue , Xiaotao Zheng

We provide a unifying treatment of pathwise moderate deviations for models commonly used in financial applications, and for related integrated functionals. Suitable scaling allows us to transfer these results into small-time, large-time and…

Mathematical Finance · Quantitative Finance 2018-12-04 Antoine Jacquier , Konstantinos Spiliopoulos

In this work we are concerned with valuing optionalities associated to invest or to delay investment in a project when the available information provided to the manager comes from simulated data of cash flows under historical (or…

Computational Finance · Quantitative Finance 2015-09-14 Edgardo Brigatti , Felipe Macias , Max O. Souza , Jorge P. Zubelli

We investigate the problem of pricing derivatives under a fractional stochastic volatility model. We obtain an approximate expression of the derivative price where the stochastic volatility can be composed of deterministic functions of time…

Pricing of Securities · Quantitative Finance 2022-10-28 Yuecai Han , Xudong Zheng

Pricing financial or real options with arbitrary payoffs in regime-switching models is an important problem in finance. Mathematically, it is to solve, under certain standard assumptions, a general form of optimal stopping problems in…

Mathematical Finance · Quantitative Finance 2018-09-11 Masahiko Egami , Rusudan Kevkhishvili

In mathematical finance, a process of calibrating stochastic volatility (SV) option pricing models to real market data involves a numerical calculation of integrals that depend on several model parameters. This optimization task consists of…

Numerical Analysis · Mathematics 2020-06-24 Josef Daněk , J. Pospíšil

We describe a high performance parallel implementation of a derivative pricing model, within which we introduce a new parallel method for the calibration of the industry standard SABR (stochastic-\alpha \beta \rho) stochastic volatility…

Distributed, Parallel, and Cluster Computing · Computer Science 2013-01-15 Qasim Nasar-Ullah