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In this article, we propose a new numerical approach to high-dimensional partial differential equations (PDEs) arising in the valuation of exotic derivative securities. The proposed method is extended from Reisinger and Wittum (2007) and…

Computational Finance · Quantitative Finance 2013-10-04 Christoph Reisinger , Rasmus Wissmann

We propose the deep parametric PDE method to solve high-dimensional parametric partial differential equations. A single neural network approximates the solution of a whole family of PDEs after being trained without the need of sample…

Computational Finance · Quantitative Finance 2020-12-14 Kathrin Glau , Linus Wunderlich

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

Using tools from spectral analysis, singular and regular perturbation theory, we develop a systematic method for analytically computing the approximate price of a derivative-asset. The payoff of the derivative-asset may be path-dependent.…

Computational Finance · Quantitative Finance 2012-04-09 Matthew Lorig

An efficient computational algorithm to price financial derivatives is presented. It is based on a path integral formulation of the pricing problem. It is shown how the path integral approach can be worked out in order to obtain fast and…

Statistical Mechanics · Physics 2009-11-07 G. Montagna , O. Nicrosini , N. Moreni

Recent progress in the development of efficient computational algorithms to price financial derivatives is summarized. A first algorithm is based on a path integral approach to option pricing, while a second algorithm makes use of a neural…

Statistical Mechanics · Physics 2009-11-07 G. Montagna , M. Morelli , O. Nicrosini , P. Amato , M. Farina

A discretization scheme for nonnegative diffusion processes is proposed and the convergence of the corresponding sequence of approximate processes is proved using the martingale problem framework. Motivations for this scheme come typically…

Computational Finance · Quantitative Finance 2010-11-16 Chantal Labbé , Bruno Rémillard , Jean-François Renaud

We study the pricing of derivative securities in financial markets modeled by a sub-mixed fractional Brownian motion with jumps (smfBm-J), a non-Markovian process that captures both long-range dependence and jump discontinuities. Under this…

Pricing of Securities · Quantitative Finance 2025-07-01 Nader Karimi

Following the recent great advance of quantum computing technology, there are growing interests in its applications to industries, including finance. In this paper, we focus on derivative pricing based on solving the Black-Scholes partial…

Quantum Physics · Physics 2021-09-28 Koichi Miyamoto , Kenji Kubo

In this article we develop an explicit formula for pricing European options when the underlying stock price follows a non-linear stochastic differential delay equation (sdde). We believe that the proposed model is sufficiently flexible to…

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

We derive a new high-order compact finite difference scheme for option pricing in stochastic volatility jump models, e.g. in Bates model. In such models the option price is determined as the solution of a partial integro-differential…

Computational Finance · Quantitative Finance 2019-02-25 Bertram Düring , Alexander Pitkin

A derivative is a financial security whose value is a function of underlying traded assets and market outcomes. Pricing a financial derivative involves setting up a market model, finding a martingale (``fair game") probability measure for…

Quantum Physics · Physics 2022-09-20 Patrick Rebentrost , Alessandro Luongo , Samuel Bosch , Seth Lloyd

Stochastic differential equation (SDE) models are the foundation for pricing and hedging financial derivatives. The drift and volatility functions in SDE models are typically chosen to be algebraic functions with a small number (less than…

Computational Finance · Quantitative Finance 2024-06-04 Lei Fan , Justin Sirignano

Employing probabilistic techniques we compute best possible upper and lower bounds on the price of an option on one or two assets with continuous piecewise linear payoff function based on prices of simple call options of possibly distinct…

Probability · Mathematics 2008-12-02 Dimitris Bertsimas , Natasha Bushueva

We consider the pricing of derivatives written on the discretely sampled realized variance of an underlying security. In the literature, the realized variance is usually approximated by its continuous-time limit, the quadratic variation of…

Pricing of Securities · Quantitative Finance 2010-11-24 Martin Keller-Ressel , Johannes Muhle-Karbe

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

In this paper we propose a new model for pricing stock and dividend derivatives. We jointly specify dynamics for the stock price and the dividend rate such that the stock price is positive and the dividend rate non-negative. In its simplest…

Mathematical Finance · Quantitative Finance 2019-08-27 Sander Willems

We develop a model for indifference pricing in derivatives markets where price quotes have bid-ask spreads and finite quantities. The model quantifies the dependence of the prices and hedging portfolios on an investor's beliefs, risk…

Pricing of Securities · Quantitative Finance 2018-03-08 John Armstrong , Teemu Pennanen , Udomsak Rakwongwan

In this paper, we present a very fast Monte Carlo scheme for additive processes: the computational time is of the same order of magnitude of standard algorithms for Brownian motions. We analyze in detail numerical error sources and propose…

Computational Finance · Quantitative Finance 2023-07-17 Michele Azzone , Roberto Baviera

In this paper we study partial differential equations (PDEs) that can be used to model value adjustments. Different value adjustments denoted generally as xVA are nowadays added to the risk-free financial derivative values and the PDE…

Risk Management · Quantitative Finance 2021-07-21 Falko Baustian , Martin Fencl , Jan Pospíšil , Vladimír Švígler
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