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Related papers: Option Pricing via Multi-path Autoregressive Monte…

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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

Option valuation problems are often solved using standard Monte Carlo (MC) methods. These techniques can often be enhanced using several strategies especially when one discretizes the dynamics of the underlying asset, of which we assume…

Computational Finance · Quantitative Finance 2018-06-06 P. P. Osei , A. Jasra

In this paper we provide a quantum Monte Carlo algorithm to solve multidimensional Black-Scholes PDEs with correlation for option pricing. The payoff function of the option is of general form and is only required to be continuous and…

Quantum Physics · Physics 2026-05-05 Jianjun Chen , Yongming Li , Ariel Neufeld

We describe the pricing and hedging of financial options without the use of probability using rough paths. By encoding the volatility of assets in an enhancement of the price trajectory, we give a pathwise presentation of the replication of…

Mathematical Finance · Quantitative Finance 2020-07-09 John Armstrong , Claudio Bellani , Damiano Brigo , Thomas Cass

The rough Bergomi (rBergomi) model, introduced recently in [5], is a promising rough volatility model in quantitative finance. It is a parsimonious model depending on only three parameters, and yet remarkably fits with empirical implied…

Computational Finance · Quantitative Finance 2020-07-13 Christian Bayer , Chiheb Ben Hammouda , Raul Tempone

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

Monte Carlo methods represent a cornerstone of computer science. They allow to sample high dimensional distribution functions in an efficient way. In this paper we consider the extension of Automatic Differentiation (AD) techniques to Monte…

High Energy Physics - Lattice · Physics 2023-07-31 Guilherme Catumba , Alberto Ramos , Bryan Zaldivar

Typically options with a path dependent payoff, such as Target Accumulation Redemption Note (TARN), are evaluated by a Monte Carlo method. This paper describes a finite difference scheme for pricing a TARN option. Key steps in the proposed…

Computational Finance · Quantitative Finance 2026-05-12 Xiaolin Luo , Pavel Shevchenko

Risk assessment and in particular derivatives pricing is one of the core areas in computational finance and accounts for a sizeable fraction of the global computing resources of the financial industry. We outline a quantum-inspired…

Quantum Physics · Physics 2022-03-08 Michael Kastoryano , Nicola Pancotti

In this paper, we have studied option pricing methods that are based on a Bayesian Markov-Switching Vector Autoregressive (MS-BVAR) process using a risk-neutral valuation approach. A BVAR process, which is a special case of the Bayesian…

Mathematical Finance · Quantitative Finance 2024-09-24 Battulga Gankhuu

We propose a methodology for computing single and multi-asset European option prices, and more generally expectations of scalar functions of (multivariate) random variables. This new approach combines the ability of Monte Carlo simulation…

Computational Finance · Quantitative Finance 2019-10-21 Damir Filipović , Kathrin Glau , Yuji Nakatsukasa , Francesco Statti

A master equation approach to the numerical solution of option pricing models is developed. The basic idea of the approach is to consider the Black--Scholes equation as the macroscopic equation of an underlying mesoscopic stochastic option…

Statistical Mechanics · Physics 2009-11-07 Daniel Faller , Francesco Petruccione

We present here a regress later based Monte Carlo approach that uses neural networks for pricing high-dimensional contingent claims. The choice of specific architecture of the neural networks used in the proposed algorithm provides for…

Computational Finance · Quantitative Finance 2019-11-27 Vikranth Lokeshwar , Vikram Bhardawaj , Shashi Jain

This paper develops three polynomial-time pricing techniques for European Asian options with provably small errors, where the stock prices follow binomial trees or trees of higher-degree. The first technique is the first known Monte Carlo…

Computational Engineering, Finance, and Science · Computer Science 2007-05-23 Karhan Akcoglu , Ming-Yang Kao , Shuba Raghavan

In this article we propose a novel approach to reduce the computational complexity of various approximation methods for pricing discrete time American options. Given a sequence of continuation values estimates corresponding to different…

Computational Finance · Quantitative Finance 2013-12-30 Denis Belomestny , Fabian Dickmann , Tigran Nagapetyan

We apply multilevel Monte Carlo for option pricing problems using exponential L\'{e}vy models with a uniform timestep discretisation to monitor the running maximum required for lookback and barrier options. The numerical results demonstrate…

Computational Finance · Quantitative Finance 2017-05-31 Mike Giles , Yuan Xia

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

In the paper, the pricing of Quanto options is studied, where the underlying foreign asset and the exchange rate are correlated with each other. Firstly, we adopt Bayesian methods to estimate unknown parameters entering the pricing formula…

Computational Finance · Quantitative Finance 2019-10-10 Lisha Lin , Yaqiong Li , Rui Gao , Jianhong Wu

Pricing a multi-asset derivative is an important problem in financial engineering, both theoretically and practically. Although it is suitable to numerically solve partial differential equations to calculate the prices of certain types of…

Quantum Physics · Physics 2022-07-05 Kenji Kubo , Koichi Miyamoto , Kosuke Mitarai , Keisuke Fujii

This thesis explores the historical progression and theoretical constructs of financial mathematics, with an in-depth exploration of Stochastic Calculus as showcased in the Binomial Asset Pricing Model and the Continuous-Time Models. A…

Computational Finance · Quantitative Finance 2024-08-13 Zheng Cao