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The validity of an approximation formula for European option prices under a general stochastic volatility model is proved in the light of the Edgeworth expansion for ergodic diffusions. The asymptotic expansion is around the Black-Scholes…

Computational Finance · Quantitative Finance 2010-04-14 Masaaki Fukasawa

This paper deals with the exact calibration of semidiscretized stochastic local volatility (SLV) models to their underlying semidiscretized local volatility (LV) models. Under an SLV model, it is common to approximate the fair value of…

Numerical Analysis · Mathematics 2016-09-02 Maarten Wyns , Karel in 't Hout

The Stochastic Volatility (SV) model and its variants are widely used in the financial sector while recurrent neural network (RNN) models are successfully used in many large-scale industrial applications of Deep Learning. Our article…

Econometrics · Economics 2022-01-25 Trong-Nghia Nguyen , Minh-Ngoc Tran , David Gunawan , R. Kohn

In this paper similar to [P. Carr, A. Itkin, 2019] we construct another Markovian approximation of the rough Heston-like volatility model - the ADO-Heston model. The characteristic function (CF) of the model is derived under both…

Computational Finance · Quantitative Finance 2023-09-27 Andrey Itkin

We provide a simple method to estimate the parameters of multivariate stochastic volatility models with latent factor structures. These models are very useful as they alleviate the standard curse of dimensionality, allowing the number of…

Econometrics · Economics 2023-02-15 Giorgio Calzolari , Roxana Halbleib , Christian Mücher

We introduce a flexible and tractable infinite-dimensional stochastic volatility model. More specifically, we consider a Hilbert space valued Ornstein-Uhlenbeck-type process, whose instantaneous covariance is given by a pure-jump stochastic…

Probability · Mathematics 2021-08-06 Sonja Cox , Sven Karbach , Asma Khedher

We develop Edgeworth expansion theory for spot volatility estimator under general assumptions on the log-price process that allow for drift and leverage effect. The result is based on further estimation of skewness and kurtosis, when…

Statistics Theory · Mathematics 2020-07-23 Lidan He , Qiang Liu , Zhi Liu

An explicit weak solution for the 3/2 stochastic volatility model is obtained and used to develop a simulation algorithm for option pricing purposes. The 3/2 model is a non-affine stochastic volatility model whose variance process is the…

Computational Finance · Quantitative Finance 2021-01-12 Iro René Kouarfate , Michael A. Kouritzin , Anne MacKay

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 presents how to apply the stochastic collocation technique to assets that can not move below a boundary. It shows that the polynomial collocation towards a lognormal distribution does not work well. Then, the potentials issues of…

Pricing of Securities · Quantitative Finance 2021-09-07 Fabien Le Floc'h , Cornelis W. Oosterlee

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

In this paper, we study stochastic volatility models in regimes where the maturity is small, but large compared to the mean-reversion time of the stochastic volatility factor. The problem falls in the class of averaging/homogenization…

Pricing of Securities · Quantitative Finance 2012-08-22 Jin Feng , Jean-Pierre Fouque , Rohini Kumar

Albeit of crucial interest for both financial practitioners and researchers, market-implied volatility data of European swaptions often exhibit large portions of missing quotes due to illiquidity of the various underlying swaption…

Machine Learning · Computer Science 2022-04-25 Ivo Richert , Robert Buch

This article presents a generic hybrid numerical method to price a wide range of options on one or several assets, as well as assets with stochastic drift or volatility. In particular for equity and interest rate hybrid with local…

Computational Finance · Quantitative Finance 2024-11-11 Olivier Deloire , Louis Roth

In order to deal with the question of the existence of a calibrated local stochastic volatility model in finance, we investigate a class of McKean--Vlasov equations where a minimal continuity assumption is imposed on the coefficients.…

Probability · Mathematics 2024-10-22 Mao Fabrice Djete

We study specific nonlinear transformations of the Black-Scholes implied volatility to show remarkable properties of the volatility surface. Model-free bounds on the implied volatility skew are given. Pricing formulas for the European…

Pricing of Securities · Quantitative Finance 2010-09-30 Masaaki Fukasawa

We present a tractable non-independent increment process which provides a high modeling flexibility. The process lies on an extension of the so-called Harris chains to continuous time being stationary and Feller. We exhibit constructions,…

Applications · Statistics 2016-05-19 Michelle Anzarut , Ramses H. Mena

After a brief review of option pricing theory, we introduce various methods proposed for extracting the statistical information implicit in options prices. We discuss the advantages and drawbacks of each method, the interpretation of their…

Condensed Matter · Physics 2007-05-23 Rama Cont

We study the local volatility function in the Foreign Exchange market where both domestic and foreign interest rates are stochastic. This model is suitable to price long-dated FX derivatives. We derive the local volatility function and…

Pricing of Securities · Quantitative Finance 2012-04-04 Griselda Deelstra , Grégory Rayée

Extracting the risk neutral density (RND) function from option prices is well defined in principle, but is very sensitive to errors in practice. For risk management, knowledge of the entire RND provides more information for Value-at-Risk…

Data Analysis, Statistics and Probability · Physics 2016-09-08 Jerome V. Healy , Maurice Dixon , Brian J. Read , Fang Fang Cai