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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

This work introduces an end-to-end framework for multi-asset option pricing that combines market-consistent risk-neutral density recovery with quantum-accelerated numerical integration. We first calibrate arbitrage-free marginal…

Computational Finance · Quantitative Finance 2026-01-08 Julien Hok , Álvaro Leitao

This paper investigates the use of multiple directions of stratification as a variance reduction technique for Monte Carlo simulations of path-dependent options driven by Gaussian vectors. The precision of the method depends on the choice…

Computational Finance · Quantitative Finance 2010-04-29 Benjamin Jourdain , Bernard Lapeyre , Piergiacomo Sabino

We propose extensions and improvements of the statistical analysis of distributed multipoles (SADM) algorithm put forth by Chipot et al. in [6] for the derivation of distributed atomic multipoles from the quantum-mechanical electrostatic…

Numerical Analysis · Mathematics 2010-07-28 Nicolas Champagnat , Christophe Chipot , Erwan Faou

We present a method to linearize, without approximation, a specific class of eigenvalue problems with eigenvector nonlinearities (NEPv), where the nonlinearities are expressed by scalar functions that are defined by a quotient of linear…

Numerical Analysis · Mathematics 2021-05-24 Rob Claes , Elias Jarlebring , Karl Meerbergen , Parikshit Upadhyaya

The approximation of a high-dimensional vector by a small combination of column vectors selected from a fixed matrix has been actively debated in several different disciplines. In this paper, a sampling approach based on the Monte Carlo…

Information Theory · Computer Science 2016-10-05 Tomoyuki Obuchi , Yoshiyuki Kabashima

Two primary scalar auxiliary variable (SAV) approaches are widely applied for simulating gradient flow systems, i.e., the nonlinear energy-based approach and the Lagrange multiplier approach. The former guarantees unconditional energy…

Numerical Analysis · Mathematics 2024-11-27 Qiong-Ao Huang , Wei Jiang , Jerry Zhijian Yang , Cheng Yuan

We develop a mixed least squares Monte Carlo-partial differential equation (LSMC-PDE) method for pricing Bermudan style options on assets whose volatility is stochastic. The algorithm is formulated for an arbitrary number of assets and…

Computational Finance · Quantitative Finance 2020-06-02 David Farahany , Kenneth Jackson , Sebastian Jaimungal

The Libor market model is a mainstay term structure model of interest rates for derivatives pricing, especially for Bermudan swaptions, and other exotic Libor callable derivatives. For numerical implementation the pricing of derivatives…

Computational Finance · Quantitative Finance 2018-09-25 Haojie Wang , Han Chen , Agus Sudjianto , Richard Liu , Qi Shen

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

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

In order to overcome the drawbacks of assuming deterministic volatility coefficients in the standard LIBOR market models to capture volatility smiles and skews in real markets, several extensions of LIBOR models to incorporate stochastic…

Pricing of Securities · Quantitative Finance 2024-08-06 A. M. Ferreiro , J. A. García , J. G. López-Salas , C. Vázquez

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

Model merging combines multiple fine-tuned models into a single model by adding their weight updates, providing a lightweight alternative to retraining. Existing methods primarily target resolving conflicts between task updates, leaving the…

Machine Learning · Computer Science 2026-05-22 Yayuan Li , Ze Peng , Jian Zhang , Jintao Guo , Yue Duan , Yinghuan Shi

We propose a method for pricing American options whose pay-off depends on the moving average of the underlying asset price. The method uses a finite dimensional approximation of the infinite-dimensional dynamics of the moving average…

Pricing of Securities · Quantitative Finance 2010-11-17 Marie Bernhart , Peter Tankov , Xavier Warin

A Monte Carlo algorithm is said to be adaptive if it automatically calibrates its current proposal distribution using past simulations. The choice of the parametric family that defines the set of proposal distributions is critical for good…

Statistics Theory · Mathematics 2011-11-11 Christian Schäfer , Nicolas Chopin

The equilibrium configuration of a plasma in an axially symmetric reactor is described mathematically by a free boundary problem associated with the celebrated Grad--Shafranov equation. The presence of uncertainty in the model parameters…

Computational Physics · Physics 2023-12-22 Howard C. Elman , Jiaxing Liang , Tonatiuh Sánchez-Vizuet

In this paper, we propose a new design method of discrete-valued control for continuous-time linear time-invariant systems based on sum-of-absolute-values (SOAV) optimization. We first formulate the discrete-valued control design as a…

Systems and Control · Computer Science 2015-09-29 Takuya Ikeda , Masaaki Nagahara , Shunsuke Ono

Using spectral decomposition techniques and singular perturbation theory, we develop a systematic method to approximate the prices of a variety of options in a fast mean-reverting stochastic volatility setting. Four examples are provided in…

Pricing of Securities · Quantitative Finance 2012-05-15 Jean-Pierre Fouque , Sebastian Jaimungal , Matthew Lorig

In this paper, we discuss a simple yet robust PDE method for evaluating path-dependent Asian-style options using the non-oscillatory forward-in-time second-order MPDATA finite-difference scheme. The valuation methodology involves casting…

Computational Finance · Quantitative Finance 2025-06-02 Paweł Magnuszewski , Sylwester Arabas
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