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Using Malliavin calculus techniques, we obtain formulas for computing Greeks under different rough Volterra stochastic volatility models. Due to the fact that underlying prices are not always square integrable, we extend the classical…

Mathematical Finance · Quantitative Finance 2025-07-08 Mishari Al-Foraih , Òscar Burés , Jan Pospíšil , Josep Vives

Stochastic differential equation (SDE) models are the foundation for pricing and hedging financial derivatives. The drift and volatility functions in SDE models are typically chosen to be algebraic functions with a small number (less than…

Computational Finance · Quantitative Finance 2024-06-04 Lei Fan , Justin Sirignano

In this paper, we price European Call three different option pricing models, where the volatility is dynamically changing i.e. non constant. In stochastic volatility (SV) models for option pricing a closed form approximation technique is…

Pricing of Securities · Quantitative Finance 2023-09-19 Natasha Latif , Shafqat Ali Shad , Muhammad Usman , Chandan Kumar , Bahman B Motii , MD Mahfuzer Rahman , Khuram Shafi , Zahra Idrees

Exact simulation schemes under the Heston stochastic volatility model (e.g., Broadie-Kaya and Glasserman-Kim) suffer from computationally expensive modified Bessel function evaluations. We propose a new exact simulation scheme without the…

Mathematical Finance · Quantitative Finance 2023-12-18 Jaehyuk Choi , Yue Kuen Kwok

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

New simulation approaches to evaluating path-dependent options without matrix inversion issues nor Euler bias are evaluated. They employ three main contributions: Stochastic approximation replaces regression in the LSM algorithm; Explicit…

Pricing of Securities · Quantitative Finance 2018-04-13 Michael A. Kouritzin

The computation of Greeks is a fundamental task for risk managing of financial instruments. The standard approach to their numerical evaluation is via finite differences. Most exotic derivatives are priced via Monte Carlo simulation: in…

Computational Finance · Quantitative Finance 2021-06-24 Andrea Maran , Andrea Pallavicini , Stefano Scoleri

We propose analytical approximations for the sensitivities (Greeks) of the Asian options in the Black-Scholes model, following from a small maturity/volatility approximation for the option prices which has the exact short maturity limit,…

Pricing of Securities · Quantitative Finance 2023-01-18 Dan Pirjol , Lingjiong Zhu

Real-time calibration of stochastic volatility models (SVMs) is computationally bottlenecked by the need to repeatedly solve coupled partial differential equations (PDEs). In this work, we propose DeepSVM, a physics-informed Deep Operator…

Computational Finance · Quantitative Finance 2025-12-09 Kieran A. Malandain , Selim Kalici , Hakob Chakhoyan

A parsimonious generalization of the Heston model is proposed where the volatility-of-volatility is assumed to be stochastic. We follow the perturbation technique of Fouque et al (2011, CUP) to derive a first order approximation of the…

Pricing of Securities · Quantitative Finance 2017-06-06 Jean-Pierre Fouque , Yuri F. Saporito

Hedging methods to mitigate the exposure of variable annuity products to market risks require the calculation of market risk sensitivities (or "Greeks"). The complex, path-dependent nature of these products means these sensitivities…

Risk Management · Quantitative Finance 2011-10-21 Mark J. Cathcart , Steven Morrison , Alexander J. McNeil

In this paper we investigate price and Greeks computation of a Guaranteed Minimum Withdrawal Benefit (GMWB) Variable Annuity (VA) when both stochastic volatility and stochastic interest rate are considered together in the Heston Hull-White…

Computational Finance · Quantitative Finance 2019-07-23 Ludovic Goudenège , Andrea Molent , Antonino Zanette

Calibration of large-scale differential equation models to observational or experimental data is a widespread challenge throughout applied sciences and engineering. A crucial bottleneck in state-of-the art calibration methods is the…

Optimization and Control · Mathematics 2021-02-23 Jon Cockayne , Andrew B. Duncan

We propose a convolution-FFT method for pricing European options under the Heston model that leverages a continuously differentiable representation of the joint characteristic function. Unlike existing Fourier-based methods that rely on…

Computational Finance · Quantitative Finance 2025-12-08 Xiang Gao , Cody Hyndman

We investigate a machine learning approach to option Greeks approximation based on Gaussian process (GP) surrogates. The method takes in noisily observed option prices, fits a nonparametric input-output map and then analytically…

Computational Finance · Quantitative Finance 2022-01-17 Mike Ludkovski , Yuri Saporito

Quasi Monte Carlo (QMC) and Global Sensitivity Analysis (GSA) techniques are applied for pricing and hedging representative financial instruments of increasing complexity. We compare standard Monte Carlo (MC) vs QMC results using Sobol' low…

Computational Finance · Quantitative Finance 2026-02-17 Stefano Scoleri , Marco Bianchetti , Sergei Kucherenko

We study the Heston model for pricing European options on stocks with stochastic volatility. This is a Black\--Scholes\--type equation whose spatial domain for the logarithmic stock price $x\in \RR$ and the variance $v\in (0,\infty)$ is the…

Analysis of PDEs · Mathematics 2017-11-15 Bénédicte Alziary , Peter Takáč

We study the use of the multilevel Monte Carlo technique in the context of the calculation of Greeks. The pathwise sensitivity analysis differentiates the path evolution and reduces the payoff's smoothness. This leads to new challenges: the…

Computational Finance · Quantitative Finance 2011-02-08 Sylvestre Burgos , M. B. Giles

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

We address the information content of European option prices about volatility in terms of the Fisher information matrix. We assume that observed option prices are centred on the theoretical price provided by Heston's model disturbed by…

Statistical Finance · Quantitative Finance 2016-10-19 Oliver Pfante , Nils Bertschinger