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We present a numerically efficient approach for learning a risk-neutral measure for paths of simulated spot and option prices up to a finite horizon under convex transaction costs and convex trading constraints. This approach can then be…

Computational Finance · Quantitative Finance 2021-07-15 Hans Buehler , Phillip Murray , Mikko S. Pakkanen , Ben Wood

We introduce a novel stochastic volatility model where the squared volatility of the asset return follows a Jacobi process. It contains the Heston model as a limit case. We show that the joint density of any finite sequence of log returns…

Mathematical Finance · Quantitative Finance 2018-10-31 Damien Ackerer , Damir Filipović , Sergio Pulido

Motivation of our work is to present a new methodology for symbol recognition. We support structural methods for representing visual associations in graphic documents. The proposed method employs a structural approach for symbol…

Computer Vision and Pattern Recognition · Computer Science 2010-05-03 Muhammad Muzzamil Luqman , Mathieu Delalandre , Thierry Brouard , Jean-Yves Ramel , Josep Lladós

This report investigates the computation of option Greeks for European and Asian options under the Heston stochastic volatility model on GPU. We first implemented the exact simulation method proposed by Broadie and Kaya and used it as a…

Computational Finance · Quantitative Finance 2023-09-20 Pierre-Antoine Arsaguet , Paul Bilokon

We introduce a new identification strategy for uncertainty shocks to explain macroeconomic volatility in financial markets. The Chicago Board Options Exchange Volatility Index (VIX) measures market expectations of future volatility, but…

Econometrics · Economics 2024-11-06 Ayush Jha , Abootaleb Shirvani , Svetlozar T. Rachev , Frank J. Fabozzi

Following closely the construction of the Schrodinger bridge, we build a new class of Stochastic Volatility Models exactly calibrated to market instruments such as for example Vanillas, options on realized variance or VIX options. These…

Computational Finance · Quantitative Finance 2019-04-10 Pierre Henry-Labordere

American put options are among the most frequently traded single stock options, and their calibration is computationally challenging since no closed-form expression is available. Due to the higher flexibility in comparison to European…

Numerical Analysis · Mathematics 2016-11-22 Olena Burkovska , Kathrin Glau , Mirco Mahlstedt , Barbara Wohlmuth

Topological methods for data analysis present opportunities for enforcing certain invariances of broad interest in computer vision, including view-point in activity analysis, articulation in shape analysis, and measurement invariance in…

Computer Vision and Pattern Recognition · Computer Science 2018-07-30 Anirudh Som , Kowshik Thopalli , Karthikeyan Natesan Ramamurthy , Vinay Venkataraman , Ankita Shukla , Pavan Turaga

This paper establishes a comprehensive concentration theory for truncated signatures of Gaussian rough paths. The signature of a path, defined as the collection of all iterated integrals, provides a complete description of its geometric…

Probability · Mathematics 2025-12-11 Atef Lechiheb

In this note we consider splitting methods based on linear multistep methods and stabilizing corrections. To enhance the stability of the methods, we employ an idea of Bruno & Cubillos (2016) who combine a high-order extrapolation formula…

Numerical Analysis · Mathematics 2017-09-05 Willem Hundsdorfer , Karel in 't Hout

This article proposes a calibration framework for complex option pricing models that jointly fits market option prices and the term structure of variance. Calibrated models under the conventional objective function, the sum of squared…

General Finance · Quantitative Finance 2025-09-11 Jiwook Yoo

In this paper we prove an approximate formula expressed in terms of elementary functions for the implied volatility in the Heston model. The formula consists of the constant and first order terms in the large maturity expansion of the…

Pricing of Securities · Quantitative Finance 2015-05-14 Martin Forde , Antoine Jacquier , Aleksandar Mijatovic

In this chapter we first briefly review the existing approaches to hedging in rough volatility models. Next, we present a simple but general result which shows that in a one-factor rough stochastic volatility model, any option may be…

Mathematical Finance · Quantitative Finance 2021-05-11 Masaaki Fukasawa , Blanka Horvath , Peter Tankov

Signatures, one of the key concepts of rough path theory, have recently gained prominence as a means to find appropriate feature sets in machine learning systems. In this paper, in order to compute signatures directly from discrete data…

Mathematical Finance · Quantitative Finance 2022-01-17 Takanori Adachi , Yusuke Naritomi

In the present work, the European option pricing SWIFT method is extended for Heston model calibration. The computation of the option price gradient is simplified thanks to the knowledge of the characteristic function in closed form. The…

Computational Finance · Quantitative Finance 2021-03-03 Eudald Romo , Luis Ortiz-Gracia

In this paper, we study the option pricing problems for rough volatility models. As the framework is non-Markovian, the value function for a European option is not deterministic; rather, it is random and satisfies a backward stochastic…

Mathematical Finance · Quantitative Finance 2020-08-05 Christian Bayer , Jinniao Qiu , Yao Yao

Exact path simulation of the underlying state variable is of great practical importance in simulating prices of financial derivatives or their sensitivities when there are no analytical solutions for their pricing formulas. However, in…

Computational Finance · Quantitative Finance 2018-08-23 Lancelot F. James , Dohyun Kim , Zhiyuan Zhang

We derive a higher-order asymptotic expansion of the conditional characteristic function of the increment of an It\^o semimartingale over a shrinking time interval. The spot characteristics of the It\^o semimartingale are allowed to have…

Statistical Finance · Quantitative Finance 2024-11-12 Carsten H. Chong , Viktor Todorov

We consider a large market model of defaultable assets in which the asset price processes are modelled as Heston-type stochastic volatility models with default upon hitting a lower boundary. We assume that both the asset prices and their…

Probability · Mathematics 2019-05-15 Ben Hambly , Nikolaos Kolliopoulos

Motivated by empirical evidence for rough volatility models, this paper investigates continuous-time mean-variance (MV) portfolio selection under the Volterra Heston model. Due to the non-Markovian and non-semimartingale nature of the…

Portfolio Management · Quantitative Finance 2020-01-30 Bingyan Han , Hoi Ying Wong