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In this work we propose a option pricing model based on the Ornstein-Uhlenbeck process. It is a new look at the Black-Scholes formula which is based on the quantum game theory. We show the differences between a classical look which is price…

Quantum Physics · Physics 2009-11-11 Edward W. Piotrowski , Malgorzata Schroeder , Anna Zambrzycka

In this paper we discuss the possibility of using multilevel Monte Carlo (MLMC) methods for weak approximation schemes. It turns out that by means of a simple coupling between consecutive time discretisation levels, one can achieve the same…

Computational Finance · Quantitative Finance 2014-10-07 Denis Belomestny , Tigran Nagapetyan

In this paper I develop a new computational method for pricing path dependent options. Using the path integral representation of the option price, I show that in general it is possible to perform analytically a partial averaging over the…

Statistical Mechanics · Physics 2016-08-31 Andrew Matacz

We introduce a new approach to quantize the Euler scheme of an $\mathbb{R}^d$-valued diffusion process. This method is based on a Markovian and componentwise product quantization and allows us, from a numerical point of view, to speak of…

Probability · Mathematics 2017-03-27 Fiorin Lucio , Gilles Pagès , Abass Sagna

We present a new numerical method to price vanilla options quickly in time-changed Brownian motion models. The method is based on rational function approximations of the Black-Scholes formula. Detailed numerical results are given for a…

Computational Finance · Quantitative Finance 2012-04-02 Martijn Pistorius , Johannes Stolte

Quantum Finance represents the synthesis of the techniques of quantum theory (quantum mechanics and quantum field theory) to theoretical and applied finance. After a brief overview of the connection between these fields, we illustrate some…

Soft Condensed Matter · Physics 2017-08-23 Belal E. Baaquie , Claudio Coriano , Marakani Srikant

This paper covers a massive acceleration of Monte-Carlo based pricing method for financial products and financial derivatives. The method is applicable in risk management settings, where a financial product has to be priced under a number…

Computational Engineering, Finance, and Science · Computer Science 2008-09-30 Stefan Dirnstorfer , Andreas J. Grau

Several cubature formulas on the cubic domains are derived using the discrete Fourier analysis associated with lattice tiling, as developed in \cite{LSX}. The main results consist of a new derivation of the Gaussian type cubature for the…

Numerical Analysis · Mathematics 2008-08-15 Huiyuan Li , Jiachang Sun , Yuan Xu

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

In this paper new analytical and numerical approaches to valuating path-dependent options of European type have been developed. The model of stochastic volatility as a basic model has been chosen. For European options we could improve the…

Pricing of Securities · Quantitative Finance 2010-09-24 Yu. A. Kuperin , P. A. Poloskov

Barrier options are one of the most widely traded exotic options on stock exchanges. In this paper, we develop a new stochastic simulation method for pricing barrier options and estimating the corresponding execution probabilities. We show…

Pricing of Securities · Quantitative Finance 2018-03-29 Keegan Mendonca , Vasileios E. Kontosakos , Athanasios A. Pantelous , Konstantin M. Zuev

There are a number of situations where, when computing prices of financial derivatives using quasi-Monte Carlo (QMC), it turns out to be beneficial to apply an orthogonal transform to the standard normal input variables. Sometimes those…

Numerical Analysis · Mathematics 2015-08-11 Christian Irrgeher , Gunther Leobacher

Combinatorial optimization with a smooth and convex objective function arises naturally in applications such as discrete mean-variance portfolio optimization, where assets must be traded in integer quantities. Although optimal solutions to…

Quantum Physics · Physics 2025-10-14 Sebastian Schlütter , Tomislav Maras , Alexander Dotterweich , Nico Piatkowski

Gau{\ss} cubature (multidimensional numerical integration) rules are the natural generalisation of the 1D Gau{\ss} rules. They are optimal in the sense that they exactly integrate polynomials of as high a degree as possible for a particular…

Numerical Analysis · Mathematics 2025-10-20 David De Wit

The expected value of some complex valued random vectors is computed by means of the indicator function of a designed experiment as known in algebraic statistics. The general theory is set-up and results are obtained for finite discrete…

Probability · Mathematics 2017-09-27 Claudia Fassino , Eva Riccomagno , Maria-Piera Rogantin

Quantum mechanics in conical space is studied by the path integral method. It is shown that the curvature effect gives rise to an effective potential in the radial path integral. It is further shown that the radial path integral in conical…

Mathematical Physics · Physics 2011-11-28 Akira Inomata , Georg Junker

We study Euler-type discrete-time schemes for the rough Heston model, which can be described by a stochastic Volterra equation (with non-Lipschtiz coefficient functions), or by an equivalent integrated variance formulation. Using weak…

Numerical Analysis · Mathematics 2022-03-08 Alexandre Richard , Xiaolu Tan , Fan Yang

In this article we consider the problem of pricing and hedging high-dimensional Asian basket options by Quasi-Monte Carlo simulation. We assume a Black-Scholes market with time-dependent volatilities and show how to compute the deltas by…

Pricing of Securities · Quantitative Finance 2015-06-29 Nicola Cufaro Petroni , Piergiacomo Sabino

The Constant Elasticity of Variance (CEV) model significantly outperforms the Black-Scholes (BS) model in forecasting both prices and options. Furthermore, the CEV model has a marked advantage in capturing basic empirical regularities such…

Computational Finance · Quantitative Finance 2018-03-29 Axel A. Araneda , Marcelo J. Villena

Classical Monte Carlo algorithms can theoretically be sped up on a quantum computer by employing amplitude estimation (AE). To realize this, an efficient implementation of state-dependent functions is crucial. We develop a straightforward…

Quantum Physics · Physics 2024-03-26 Mark-Oliver Wolf , Tom Ewen , Ivica Turkalj
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