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Related papers: The Chebyshev method for the implied volatility

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In financial terms, an implied volatility surface can be described by its term structure, its skewness and its overall volatility level. We use a PCA variational auto-encoder model to perfectly represent these descriptors into a latent…

Pricing of Securities · Quantitative Finance 2023-06-09 Zheng Gong , Wojciech Frys , Renzo Tiranti , Carmine Ventre , John O'Hara , Yingbo Bai

Invariant inference algorithms such as interpolation-based inference and IC3/PDR show that it is feasible, in practice, to find inductive invariants for many interesting systems, but non-trivial upper bounds on the computational complexity…

Programming Languages · Computer Science 2022-08-17 Yotam M. Y. Feldman , Sharon Shoham

This article is concerned with an extension of univariate Chebyshev polynomials of the first kind to the multivariate setting, where one chases best approximants to specific monomials by polynomials of lower degree relative to the uniform…

Optimization and Control · Mathematics 2024-10-29 Mareike Dressler , Simon Foucart , Mioara Joldes , Etienne de Klerk , Jean Bernard Lasserre , Yuan Xu

Iterative methods for the simultaneous determination of all roots of an equation are dis-cussed. The multiplicities of the roots are assumed to be known in advance. The methods are proved to have a cubical rate of convergence. Numerical…

Numerical Analysis · Mathematics 2025-10-20 A. I. Iliev , Kh. I. Semerdzhiev

In a recent paper "Deep Learning Volatility" a fast 2-step deep calibration algorithm for rough volatility models was proposed: in the first step the time consuming mapping from the model parameter to the implied volatilities is learned by…

Computational Finance · Quantitative Finance 2020-07-08 Dirk Roeder , Georgi Dimitroff

This paper revisits the fractional cointegrating relationship between ex-ante implied volatility and ex-post realized volatility. We argue that the concept of corridor implied volatility (CIV) should be used instead of the popular…

Statistical Finance · Quantitative Finance 2013-02-15 Jozef Barunik , Michaela Barunikova

In applied mathematics, especially in optimization, functions are often only provided as so called "Black-Boxes" provided by software packages, or very complex algorithms, which make automatic differentation very complicated or even…

Numerical Analysis · Mathematics 2021-02-05 Stefan H. Reiterer

Recent empirical studies suggest that the volatility of an underlying price process may have correlations that decay slowly under certain market conditions. In this paper, the volatility is modeled as a stationary process with long-range…

Pricing of Securities · Quantitative Finance 2018-04-17 Josselin Garnier , Knut Solna

Missing data is a common problem in finance and often requires methods to fill in the gaps, or in other words, imputation. In this work, we focused on the imputation of missing implied volatilities for FX options. Prior work has used…

Statistical Finance · Quantitative Finance 2024-11-12 Achintya Gopal

In this paper we develop numerical pricing methodologies for European style Exchange Options written on a pair of correlated assets, in a market with finite liquidity. In contrast to the standard multi-asset Black-Scholes framework, trading…

Pricing of Securities · Quantitative Finance 2020-06-16 Kevin S. Zhang , Traian A. Pirvu

The Empirical Interpolation Method (EIM) is a greedy procedure that constructs approximate representations of two-variable functions in separated form. In its classical presentation, the two variables play a non-symmetric role. In this…

Numerical Analysis · Mathematics 2019-08-12 Fabien Casenave , Alexandre Ern , Tony Lelièvre

Monte Carlo is a simple and flexible tool that is widely used in computational finance. In this context, it is common for the quantity of interest to be the expected value of a random variable defined via a stochastic differential equation.…

Numerical Analysis · Mathematics 2015-05-06 Desmond J. Higham

We consider approximate pricing formulas for European options based on approximating the logarithmic return's density of the underlying by a linear combination of rescaled Hermite polynomials. The resulting models, that can be seen as…

Pricing of Securities · Quantitative Finance 2023-08-15 Carlo Marinelli , Stefano d'Addona

This work generalizes the subdiffusive Black-Scholes model by introducing the variable exponent in order to provide adequate descriptions for the option pricing, where the variable exponent may account for the variation of the memory…

Numerical Analysis · Mathematics 2025-10-22 Meihui Zhang , Yaxue Liu , Mengmeng Liu , Wenlin Qiu , Xiangcheng Zheng

Extracting market expectations has always been an important issue when making national policies and investment decisions in financial markets. In option markets, the most popular way has been to extract implied volatilities to assess the…

Pricing of Securities · Quantitative Finance 2009-01-05 Abel Rodriguez , Enrique ter Horst

The aim of this paper is to present a simple stochastic model that accounts for the effects of a long-memory in volatility on option pricing. The starting point is the stochastic Black-Scholes equation involving volatility with long-range…

Other Condensed Matter · Physics 2008-12-02 Sergei Fedotov , Abby Tan

G-expectation, as a sublinear expectation, provides a powerful framework for modeling uncertainty in financial markets. Motivated by the need for robust valuation under model uncertainty, this work develops a unified risk-neutral valuation…

Computational Engineering, Finance, and Science · Computer Science 2026-03-25 Ziting Pei , Xingye Yue , Xiaotao Zheng

A simple method is proposed to estimate the instantaneous correlations between state variables in a hybrid system from the empirical correlations between observable market quantities such as spot rate, stock price and implied volatility.…

Computational Finance · Quantitative Finance 2023-07-10 Baron Law

Equity basket correlation can be estimated both using the physical measure from stock prices, and also using the risk neutral measure from option prices. The difference between the two estimates motivates a so-called "dispersion strategy''.…

Statistical Finance · Quantitative Finance 2020-09-22 Wolfgang Karl Härdle , Elena Silyakova

We propose a new static parameterization of the implied volatility surface which is constructed by using polynomials of sigmoid functions combined with some other terms. This parameterization is flexible enough to fit market implied…

Mathematical Finance · Quantitative Finance 2014-12-09 Andrey Itkin