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Joint calibration to SPX and VIX market data is a delicate task that requires sophisticated modeling and incurs significant computational costs. The latter is especially true when pricing of volatility derivatives hinges on nested Monte…

Computational Finance · Quantitative Finance 2025-07-15 Fabio Baschetti , Giacomo Bormetti , Pietro Rossi

We propose a new model for the forecasting of both the implied volatility surfaces and the underlying asset price. In the spirit of Guyon and Lekeufack (2023) who are interested in the dependence of volatility indices (e.g. the VIX) on the…

Computational Finance · Quantitative Finance 2025-10-15 Hervé Andrès , Alexandre Boumezoued , Benjamin Jourdain

We explore a link between stochastic volatility (SV) and path-dependent volatility (PDV) models. Using assumed density filtering, we map a given SV model into a corresponding PDV representation. The resulting specification is lightweight,…

Mathematical Finance · Quantitative Finance 2025-10-03 Samuel N. Cohen , Cephas Svosve

Guyon and Lekeufack recently proposed a path-dependent volatility model and documented its excellent performance in fitting market data and capturing stylized facts. The instantaneous volatility is modeled as a linear combination of two…

Pricing of Securities · Quantitative Finance 2024-07-03 Marcel Nutz , Andrés Riveros Valdevenito

We consider the joint SPX-VIX calibration within a general class of Gaussian polynomial volatility models in which the volatility of the SPX is assumed to be a polynomial function of a Gaussian Volterra process defined as a stochastic…

Mathematical Finance · Quantitative Finance 2024-12-17 Eduardo Abi Jaber , Camille Illand , Shaun , Li

We regard options on VIX and Realised Variance as solutions to path-dependent partial differential equations (PDEs) in a continuous stochastic volatility model. The modeling assumption specifies that the instantaneous variance is a $C^3$…

Probability · Mathematics 2025-07-22 Alexandre Pannier

We present a fast and robust calibration method for stochastic volatility models that admit Fourier-analytic transform-based pricing via characteristic functions. The design is structure-preserving: we keep the original pricing transform…

Computational Finance · Quantitative Finance 2025-10-23 Keyuan Wu , Tenghan Zhong , Yuxuan Ouyang

We propose a new framework for modeling stochastic local volatility, with potential applications to modeling derivatives on interest rates, commodities, credit, equity, FX etc., as well as hybrid derivatives. Our model extends the…

Pricing of Securities · Quantitative Finance 2013-03-29 Igor Halperin , Andrey Itkin

This study provides a consistent and efficient pricing method for both Standard & Poor's 500 Index (SPX) options and the Chicago Board Options Exchange's Volatility Index (VIX) options under a multiscale stochastic volatility model. To…

Mathematical Finance · Quantitative Finance 2019-09-24 Jaegi Jeon , Geonwoo Kim , Jeonggyu Huh

We present an empirical study examining several claims related to option prices in rough volatility literature using SPX options data. Our results show that rough volatility models with the parameter $H \in (0,1/2)$ are inconsistent with…

Mathematical Finance · Quantitative Finance 2025-04-10 Eduardo Abi Jaber , Shaun , Li

We propose a novel and generic calibration technique for four-factor foreign-exchange hybrid local-stochastic volatility models with stochastic short rates. We build upon the particle method introduced by Guyon and Labord\`ere [Nonlinear…

Mathematical Finance · Quantitative Finance 2025-11-19 Andrei Cozma , Matthieu Mariapragassam , Christoph Reisinger

We provide explicit small-time formulae for the at-the-money implied volatility, skew and curvature in a large class of models, including rough volatility models and their multi-factor versions. Our general setup encompasses both European…

Mathematical Finance · Quantitative Finance 2023-11-15 Antoine Jacquier , Aitor Muguruza , Alexandre Pannier

The quadratic rough Heston model provides a natural way to encode Zumbach effect in the rough volatility paradigm. We apply multi-factor approximation and use deep learning methods to build an efficient calibration procedure for this model.…

Computational Finance · Quantitative Finance 2022-05-31 Mathieu Rosenbaum , Jianfei Zhang

We consider option pricing using a discrete-time Markov switching stochastic volatility with co-jump model, which can model volatility clustering and varying mean-reversion speeds of volatility. For pricing European options, we develop a…

Pricing of Securities · Quantitative Finance 2020-06-29 Michael C. Fu , Bingqing Li , Rongwen Wu , Tianqi Zhang

In this paper, we give a numerical method for pricing long maturity, path dependent options by using the Markov property for each underlying asset. This enables us to approximate a path dependent option by using some kinds of plain…

Pricing of Securities · Quantitative Finance 2009-12-01 Yuji Hishida , Kenji Yasutomi

We propose a new financial model, the stochastic volatility model with sticky drawdown and drawup processes (SVSDU model), which enables us to capture the features of winning and losing streaks that are common across financial markets but…

Mathematical Finance · Quantitative Finance 2025-03-20 Yuhao Liu , Pingping Jiang , Gongqiu Zhang

In this paper new analytical and numerical approaches to valuating path-dependent options of European type have been developed. The model of stochastic volatility as a basic model has been chosen. For European options we could improve the…

Pricing of Securities · Quantitative Finance 2010-09-24 Yu. A. Kuperin , P. A. Poloskov

We apply vector quantisation within mixed one- and two-factor Bergomi models to implement a fast and efficient approach for option pricing in these models. This allows us to calibrate such models to market data of VIX futures and options.…

Pricing of Securities · Quantitative Finance 2025-07-01 Nelson Kyakutwika , Mesias Alfeus , Erik Schlögl

We propose a generic calibration framework to both vanilla and no-touch options for a large class of continuous semi-martingale models. The method builds upon the forward partial integro-differential equation (PIDE) derived in Hambly et al.…

Mathematical Finance · Quantitative Finance 2025-11-19 Alan Bain , Matthieu Mariapragassam , Christoph Reisinger

This paper shows how to recover a stochastic volatility model (SVM) from a market model of the VIX futures term structure. Market models have more flexibility for fitting of curves than do SVMs, and therefore are better suited for pricing…

Pricing of Securities · Quantitative Finance 2022-03-16 Andrew Papanicolaou
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