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In the context of a Black-Scholes economy and with a no-arbitrage argument, we derive arbitrarily accurate lower and upper bounds for the value of European options on a stock paying a discrete dividend. Setting the option price error below…

Probability · Mathematics 2016-08-16 João Amaro de Matos , Rui Dilão , Bruno Ferreira

We consider assets for which price $X_t$ and squared volatility $Y_t$ are jointly driven by Heston joint stochastic differential equations (SDEs). When the parameters of these SDEs are estimated from $N$ sub-sampled data $(X_{nT}, Y_{nT})$,…

Mathematical Finance · Quantitative Finance 2015-07-22 Robert Azencott , Yutheeka Gadhyan , Roland Glowinski

This paper performs the numerical analysis and the computation of a Spread option in a market with imperfect liquidity. The number of shares traded in the stock market has a direct impact on the stock's price. Thus, we consider a…

Pricing of Securities · Quantitative Finance 2016-11-25 Ahmad Reza Yazdanian , T A Pirvu

We introduce a new method to price American options based on Chebyshev interpolation. In each step of a dynamic programming time-stepping we approximate the value function with Chebyshev polynomials. The key advantage of this approach is…

Computational Finance · Quantitative Finance 2018-06-15 Kathrin Glau , Mirco Mahlstedt , Christian Pötz

We present an adaptive approach for valuing the European call option on assets with stochastic volatility. The essential feature of the method is a reduction of uncertainty in latent volatility due to a Bayesian learning procedure. Starting…

Other Condensed Matter · Physics 2008-12-02 Sergei Fedotov , Stephanos Panayides

This paper develops a probabilistic numerical method for solution of partial differential equations (PDEs) and studies application of that method to PDE-constrained inverse problems. This approach enables the solution of challenging inverse…

Methodology · Statistics 2017-07-12 Jon Cockayne , Chris Oates , Tim Sullivan , Mark Girolami

In this paper, we present an implicit finite difference method for the numerical solution of the Black-Scholes model of American put options without dividend payments. We combine the proposed numerical method by using a front fixing…

Numerical Analysis · Mathematics 2020-04-09 Riccardo Fazio , Alessandra Insana , Alessandra Jannelli

We continue a series of papers where prices of the barrier options written on the underlying, which dynamics follows some one factor stochastic model with time-dependent coefficients and the barrier, are obtained in semi-closed form, see…

Computational Finance · Quantitative Finance 2020-05-13 Peter Carr , Andrey Itkin , Dmitry Muravey

The approach that allows find European option price on the assumption of hedging at discrete times is proposed. The routine allows find the option price not for lognormal distribution functions of underlying asset only but for wide enough…

Probability · Mathematics 2008-12-02 D. E. Yakovlev , D. N. Zhabin

We consider the problem of computing upper and lower bounds on the price of a European basket call option, given prices on other similar baskets. Although this problem is very hard to solve exactly in the general case, we show that in some…

Optimization and Control · Mathematics 2008-12-10 Alexandre d'Aspremont , Laurent El Ghaoui

Our goal is to analyze the system of Hamilton-Jacobi-Bellman equations arising in derivative securities pricing models. The European style of an option price is constructed as a difference of the certainty equivalents to the value functions…

Analysis of PDEs · Mathematics 2021-08-31 Pedro Polvora , Daniel Sevcovic

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

In incomplete financial markets, pricing and hedging European options lack a unique no-arbitrage solution due to unhedgeable risks. This paper introduces a constrained deep learning approach to determine option prices and hedging strategies…

Computational Finance · Quantitative Finance 2025-11-27 Nicolas Baradel

The numerical solution of differential equations can be formulated as an inference problem to which formal statistical approaches can be applied. However, nonlinear partial differential equations (PDEs) pose substantial challenges from an…

Numerical Analysis · Mathematics 2021-08-26 Junyang Wang , Jon Cockayne , Oksana Chkrebtii , T. J. Sullivan , Chris. J. Oates

We present new numerical schemes for pricing perpetual Bermudan and American options as well as $\alpha$-quantile options. This includes a new direct calculation of the optimal exercise barrier for early-exercise options. Our approach is…

Computational Finance · Quantitative Finance 2021-06-14 Carolyn E. Phelan , Daniele Marazzina , Guido Germano

We suggest a simple reduction of pricing European options in affine jump-diffusion models to pricing options with modified payoffs in diffusion models. The procedure is based on the conjugation of the infinitesimal generator of the model…

Computational Finance · Quantitative Finance 2019-12-30 Svetlana Boyarchenko , Sergei Levendorskiĭ

Fourier pricing methods such as the Carr-Madan formula or the COS method are classic tools for pricing European options for advanced models such as the Heston model. These methods require tuning parameters such as a damping factor, a…

Mathematical Finance · Quantitative Finance 2024-12-09 Gero Junike , Hauke Stier

In this paper, we propose a semi-analytical approach to pricing options on SOFR futures where the underlying SOFR follows a time-dependent CEV model. By definition, these options change their type at the beginning of the reference period:…

Computational Finance · Quantitative Finance 2024-10-08 Andrey Itkin , Yerkin Kitapbayev

There have been extensive studies on solving differential equations using physics-informed neural networks. While this method has proven advantageous in many cases, a major criticism lies in its lack of analytical error bounds. Therefore,…

Neural and Evolutionary Computing · Computer Science 2022-07-05 Shuheng Liu , Xiyue Huang , Pavlos Protopapas

This paper addresses an important gap in rigorous numerical treatments for pricing American options under correlated two-asset jump-diffusion models using the viscosity solution framework, with a particular focus on the Merton model. The…

Computational Finance · Quantitative Finance 2025-04-11 Hao Zhou , Duy-Minh Dang
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