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We consider stochastic volatility models using piecewise constant parameters. We suggest a hybrid optimization algorithm for fitting the models to a volatility surface and provide some numerical results. Finally, we provide an outlook on…

Pricing of Securities · Quantitative Finance 2010-10-07 Wolfgang Putschoegl

It is known that the implied volatility skew of FX options demonstrates a stochastic behavior which is called stochastic skew. In this paper we create stochastic skew by assuming the spot/instantaneous variance correlation to be stochastic.…

Computational Finance · Quantitative Finance 2017-01-20 Andrey Itkin

Nonlinear dynamical stochastic models are ubiquitous in different areas. Excitable media models are typical examples with large state dimensions. Their statistical properties are often of great interest but are also very challenging to…

Statistics Theory · Mathematics 2019-01-29 Nan Chen , Andrew J. Majda , Xin T. Tong

It has often been stated that, within the class of continuous stochastic volatility models calibrated to vanillas, the price of a VIX future is maximized by the Dupire local volatility model. In this article we prove that this statement is…

Mathematical Finance · Quantitative Finance 2019-10-15 Beatrice Acciaio , Julien Guyon

This paper proposes a semiparametric stochastic volatility (SV) model that relaxes the restrictive Gaussian assumption in both the return and volatility error terms, allowing them to follow flexible, nonparametric distributions with…

Computation · Statistics 2025-06-03 Yudong Feng , Ashis Gangopadhyay

We propose a fully data-driven approach to calibrate local stochastic volatility (LSV) models, circumventing in particular the ad hoc interpolation of the volatility surface. To achieve this, we parametrize the leverage function by a family…

Computational Finance · Quantitative Finance 2020-09-30 Christa Cuchiero , Wahid Khosrawi , Josef Teichmann

The calibration of a local volatility models to a given set of option prices is a classical problem of mathematical finance. It was considered in multiple papers where various solutions were proposed. In this paper an extension of the…

Computational Finance · Quantitative Finance 2016-08-19 Andrey Itkin , Alexander Lipton

Stochastic optimization problems often involve data distributions that change in reaction to the decision variables. This is the case for example when members of the population respond to a deployed classifier by manipulating their features…

Optimization and Control · Mathematics 2020-12-15 Dmitriy Drusvyatskiy , Lin Xiao

We consider an asset whose risk-neutral dynamics are described by a general class of local-stochastic volatility models and derive a family of asymptotic expansions for European-style option prices and implied volatilities. Our implied…

Computational Finance · Quantitative Finance 2014-12-01 Matthew Lorig , Stefano Pagliarani , Andrea Pascucci

In this paper, we show that a time-dependent local stochastic volatility (SLV) model can be reduced to a system of autonomous PDEs that can be solved using the Heat kernel, by means of the Wei-Norman factorization method and Lie algebraic…

Mathematical Finance · Quantitative Finance 2022-01-28 Julio Guerrero , Giuseppe Orlando

Volatility for financial assets returns can be used to gauge the risk for financial market. We propose a deep stochastic volatility model (DSVM) based on the framework of deep latent variable models. It uses flexible deep learning models to…

Machine Learning · Computer Science 2021-02-26 Xiuqin Xu , Ying Chen

This study presents contemporaneous modeling of asset return and price range within the framework of stochastic volatility with leverage. A new representation of the probability density function for the price range is provided, and its…

Computation · Statistics 2021-10-28 Yuta Kurose

The pricing of derivatives tied to baskets of assets demands a sophisticated framework that aligns with the available market information to capture the intricate non-linear dependency structure among the assets. We describe the dynamics of…

Computational Finance · Quantitative Finance 2025-10-13 Nicola F. Zaugg , Lech A. Grzelak

Most models for barrier pricing are designed to let a market maker tune the model-implied covariance between moves in the asset spot price and moves in the implied volatility skew. This is often implemented with a local…

Pricing of Securities · Quantitative Finance 2014-04-16 Mark Higgins

In this paper we consider a variety of procedures for numerical statistical inference in the family of univariate and multivariate stable distributions. In connection with univariate distributions (i) we provide approximations by finite…

Computation · Statistics 2012-09-04 Efthymios G. Tsionas

Calibration of stochastic local volatility (SLV) models to their underlying local volatility model is often performed by numerically solving a two-dimensional non-linear forward Kolmogorov equation. We propose a novel finite volume (FV)…

Numerical Analysis · Mathematics 2016-11-10 Maarten Wyns , Jacques Du Toit

We consider a structural stochastic volatility model for the loss from a large portfolio of credit risky assets. Both the asset value and the volatility processes are correlated through systemic Brownian motions, with default determined by…

Probability · Mathematics 2026-03-24 Ben Hambly , Nikolaos Kolliopoulos

Pricing storage operation in the real-time market under demand and generation stochasticities is considered. A scenario-based stochastic rolling-window dispatch model is formulated for the real-time market, consisting of conventional…

Systems and Control · Electrical Eng. & Systems 2022-10-20 Cong Chen , Lang Tong

This article describes a model and an exact solution method for facility location problems with decision-dependent uncertainties. The model allows characterizing the probability distribution of the random elements as a function of the…

Optimization and Control · Mathematics 2025-09-15 Giovanni Pantuso

We consider a portfolio optimisation problem for a utility-maximising investor who faces convex constraints on his portfolio allocation in Heston's stochastic volatility model. We apply the duality methods developed in previous work to…

Portfolio Management · Quantitative Finance 2023-11-08 Marcos Escobar-Anel , Michel Kschonnek , Rudi Zagst