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In this paper we introduce a new technique based on high-dimensional Chebyshev Tensors that we call \emph{Orthogonal Chebyshev Sliding Technique}. We implemented this technique inside the systems of a tier-one bank, and used it to…

Risk Management · Quantitative Finance 2020-12-11 Mariano Zeron-Medina Laris , Ignacio Ruiz

Financial institutions now face the important challenge of having to do multiple portfolio revaluations for their risk computation. The list is almost endless: from XVAs to FRTB, stress testing programs, etc. These computations require from…

Risk Management · Quantitative Finance 2018-05-03 Mariano Zeron Medina Laris , Ignacio Ruiz

The computation of Greeks is a fundamental task for risk managing of financial instruments. The standard approach to their numerical evaluation is via finite differences. Most exotic derivatives are priced via Monte Carlo simulation: in…

Computational Finance · Quantitative Finance 2021-06-24 Andrea Maran , Andrea Pallavicini , Stefano Scoleri

We present a comprehensive quantum algorithm tailored for pricing autocallable options, offering a full implementation and experimental validation. Our experiments include simulations conducted on high-performance computing (HPC) hardware,…

This article prices OTC derivatives with either an exogenously determined initial margin profile or endogenously approximated initial margin. In the former case, margin valuation adjustment (MVA) is defined as the liability-side discounted…

Pricing of Securities · Quantitative Finance 2020-05-05 Wujiang Lou

Pricing of financial derivatives, in particular early exercisable options such as Bermudan options, is an important but heavy numerical task in financial institutions, and its speed-up will provide a large business impact. Recently,…

Quantum Physics · Physics 2021-08-23 Koichi Miyamoto

A novel method which is called the Chebyshev inertial iteration for accelerating the convergence speed of fixed-point iterations is presented. The Chebyshev inertial iteration can be regarded as a valiant of the successive over relaxation…

Optimization and Control · Mathematics 2021-06-09 Tadashi Wadayama , Satoshi Takabe

Computational efficiency is essential for enhancing the accuracy and practicality of pricing complex financial derivatives. In this paper, we discuss Isogeometric Analysis (IGA) for valuing financial derivatives, modeled by two nonlinear…

Computational Finance · Quantitative Finance 2024-12-13 Rakhymzhan Kazbek , Yogi Erlangga , Yerlan Amanbek , Dongming Wei

Evaluating financial products with early-termination clauses, in particular those with path-dependent structures, is challenging. This paper focuses on Asian options, look-back options, and callable certificates. We will compare regression…

Pricing of Securities · Quantitative Finance 2025-07-21 Matteo Gambara , Giulia Livieri , Andrea Pallavicini

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

Trace estimators allow to approximate thermodynamic equilibrium observables with astonishing accuracy. A prominent representative is the finite-temperature Lanczos method (FTLM) which relies on a Krylov space expansion of the exponential…

Strongly Correlated Electrons · Physics 2021-12-07 H. Schlüter , F. Gayk , H. -J. Schmidt , A. Honecker , J. Schnack

This paper presents how to use Chebyshev Tensors to compute dynamic sensitivities of financial instruments within a Monte Carlo simulation. Dynamic sensitivities are then used to compute Dynamic Initial Margin as defined by ISDA (SIMM). The…

Risk Management · Quantitative Finance 2020-11-10 Mariano Zeron , Ignacio Ruiz

A spectral integral method (IEM) for solving the two-body Schroedinger equation in configuration space is generalized to the calculation of the corresponding T-matrix. It is found that the desirable features of the IEM, such as the economy…

Computational Physics · Physics 2009-11-13 George Rawitscher

Bootstrap is a popular methodology for simulating input uncertainty. However, it can be computationally expensive when the number of samples is large. We propose a new approach called \textbf{Orthogonal Bootstrap} that reduces the number of…

Methodology · Statistics 2024-05-02 Kaizhao Liu , Jose Blanchet , Lexing Ying , Yiping Lu

We propose a fast and stable method for constructing matrix approximations to fractional integral operators applied to series in the Chebyshev fractional polynomials. This method utilizes a recurrence relation satisfied by the fractional…

Numerical Analysis · Mathematics 2025-10-31 Xiaolin Liu , Kuan Xu

Elliptic Curve Cryptography (ECC) is widely accepted for ensuring secure data exchange between resource-limited IoT devices. The National Institute of Standards and Technology (NIST) recommended implementation, such as B-163, is…

Hardware Architecture · Computer Science 2025-06-17 Ruby Kumari , Tapas Rout , Babul Saini , Jai Gopal Pandey , Abhijit Karmakar

We compare exponential-type integrators for the numerical time-propagation of the equations of motion arising in the multi-configuration time-dependent Hartree-Fock method for the approximation of the high-dimensional multi-particle…

Numerical Analysis · Mathematics 2019-05-15 Winfried Auzinger , Alexander Grosz , Harald Hofstätter , Othmar Koch

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 develop a spectral method for solving univariate singular integral equations over unions of intervals by utilizing Chebyshev and ultraspherical polynomials to reformulate the equations as almost-banded infinite-dimensional systems. This…

Numerical Analysis · Mathematics 2016-12-12 Richard Mikael Slevinsky , Sheehan Olver

For large-scale eigenvalue problems requiring many mutually orthogonal eigenvectors, traditional numerical methods suffer substantial computational and communication costs with limited parallel scalability, primarily due to explicit…

Numerical Analysis · Mathematics 2026-01-12 Shengyue Wang , Aihui Zhou
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