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The double Heston model is one of the most popular option pricing models in financial theory. It is applied to several issues such that risk management and volatility surface calibration. This paper deals with the problem of global…

Statistics Theory · Mathematics 2025-01-29 Mohamed Ben Alaya , Houssem Dahbi , Hamdi Fathallah

Most of the empirical studies on stochastic volatility dynamics favor the 3/2 specification over the square-root (CIR) process in the Heston model. In the context of option pricing, the 3/2 stochastic volatility model is reported to be able…

Pricing of Securities · Quantitative Finance 2015-05-01 Wendong Zheng , Pingping Zeng

We consider estimation of the parameters of a Gaussian Stochastic Process (GaSP), in the context of emulation (approximation) of computer models for which the outcomes are real-valued scalars. The main focus is on estimation of the GaSP…

Statistics Theory · Mathematics 2017-08-17 Mengyang Gu , Xiaojing Wang , James O. Berger

Valuing Guaranteed Lifelong Withdrawal Benefit (GLWB) has attracted significant attention from both the academic field and real world financial markets. As remarked by Forsyth and Vetzal the Black and Scholes framework seems to be…

Pricing of Securities · Quantitative Finance 2019-10-21 Ludovic Goudenege , Andrea Molent , Antonino Zanette

For a large class of variational quantum circuits, we show how arbitrary-order derivatives can be analytically evaluated in terms of simple parameter-shift rules, i.e., by running the same circuit with different shifts of the parameters. As…

Quantum Physics · Physics 2021-03-03 Andrea Mari , Thomas R. Bromley , Nathan Killoran

Valuation of Credit Valuation Adjustment (CVA) has become an important field as its calculation is required in Basel III, issued in 2010, in the wake of the credit crisis. Exposure, which is defined as the potential future loss of a default…

Computational Finance · Quantitative Finance 2014-12-12 Q. Feng , C. W. Oosterlee

Rough volatility models are known to reproduce the behavior of historical volatility data while at the same time fitting the volatility surface remarkably well, with very few parameters. However, managing the risks of derivatives under…

Mathematical Finance · Quantitative Finance 2017-03-16 Omar El Euch , Mathieu Rosenbaum

We develop a GMM approach for estimation of log-normal stochastic volatility models driven by a fractional Brownian motion with unrestricted Hurst exponent. We show that a parameter estimator based on the integrated variance is consistent…

Statistical Finance · Quantitative Finance 2026-01-16 Anine E. Bolko , Kim Christensen , Mikko S. Pakkanen , Bezirgen Veliyev

The ability of Gaussian processes (GPs) to predict the behavior of dynamical systems as a more sample-efficient alternative to parametric models seems promising for real-world robotics research. However, the computational complexity of GPs…

Robotics · Computer Science 2022-03-01 Abdolreza Taheri , Joni Pajarinen , Reza Ghabcheloo

In this paper, we develop a 4/2 stochastic volatility plus jumps model, namely, a new stochastic volatility model including the Heston model and 3/2 model as special cases. Our model is highly tractable by applying the Lie symmetries theory…

Computational Finance · Quantitative Finance 2015-11-05 Wei Lin , Shenghong Li , Xingguo Luo , Shane Chern

Geometric Asian options are a type of options where the payoff depends on the geometric mean of the underlying asset over a certain period of time. This paper is concerned with the pricing of such options for the class of Volterra-Heston…

Pricing of Securities · Quantitative Finance 2025-01-14 Florian Aichinger , Sascha Desmettre

In the first part of this thesis, we focus on American options in the Heston model. We first give an analytical characterization of the value function of an American option as the unique solution of the associated (degenerate) parabolic…

Probability · Mathematics 2019-11-13 Giulia Terenzi

Discrete optimization is a central problem in artificial intelligence. The optimization of the aggregated cost of a network of cost functions arises in a variety of problems including (W)CSP, DCOP, as well as optimization in stochastic…

Artificial Intelligence · Computer Science 2018-01-12 Ferdinando Fioretto , Enrico Pontelli , William Yeoh , Rina Dechter

In this paper we derive a efficient Monte Carlo approximation for the price of path-dependent derivatives under the multiscale stochastic volatility models of Fouque \textit{et al}. Using the formulation of this pricing problem under the…

Computational Finance · Quantitative Finance 2020-05-12 Yuri F. Saporito

We consider Heston's (1993) stochastic volatility model for valuation of European options to which (semi) closed form solutions are available and are given in terms of characteristic functions. We prove that the class of scale-parameter…

Pricing of Securities · Quantitative Finance 2021-01-12 Ben Boukai

In this paper, we study the computation of sensitivities with respect to spot of path dependent financial derivatives by means of path weighting. We propose explicit path weighting formula and variance reduction adjustment in order to…

Probability · Mathematics 2024-11-21 Liu Xuan , Gauthier Michel

Classical solvable stochastic volatility models (SVM) use a CEV process for instantaneous variance where the CEV parameter $\gamma$ takes just few values: 0 - the Ornstein-Uhlenbeck process, 1/2 - the Heston (or square root) process, 1-…

Pricing of Securities · Quantitative Finance 2012-07-03 Andrey Itkin

In this paper, the valuation of European and path-dependent options in foreign exchange (FX) markets is considered when the currency exchange rate evolves according to the Heston model combined with the Cox-Ingersoll-Ross dynamics for the…

Computational Finance · Quantitative Finance 2016-04-06 Andrei Cozma , Christoph Reisinger

We present an analytic approach to solve a degenerate parabolic problem associated to the Heston model, which is widely used in mathematical finance to derive the price of an European option on an risky asset with stochastic volatility. We…

Analysis of PDEs · Mathematics 2014-06-10 A. Canale , R. M. Mininni , A. Rhandi

In this paper, we compare the intrusive proper orthogonal decomposition (POD) with Galerkin projection and the data-driven dynamic mode decomposition (DMD), for Heston's option pricing model. The full order model is obtained by…

Numerical Analysis · Mathematics 2025-01-03 Sinem Kozpınar , Murat Uzunca , Bülent Karasözen