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In the present work, we propose a new multifactor stochastic volatility model in which slow factor of volatility is approximated by a parabolic arc. We retain ourselves to the perturbation technique to obtain approximate expression for…

Pricing of Securities · Quantitative Finance 2017-04-03 Gifty Malhotra , R. Srivastava , H. C. Taneja

Recent studies have demonstrated the efficiency of Variational Autoencoders (VAE) to compress high-dimensional implied volatility surfaces into a low dimensional representation. Although this method can be effectively used for pricing…

Computational Finance · Quantitative Finance 2022-12-09 Sándor Kunsági-Máté , Gábor Fáth , István Csabai , Gábor Molnár-Sáska

We consider the pricing of derivatives in a setting with trading restrictions, but without any probabilistic assumptions on the underlying model, in discrete and continuous time. In particular, we assume that European put or call options…

Mathematical Finance · Quantitative Finance 2015-06-09 Alexander M. G. Cox , Zhaoxu Hou , Jan Obloj

In this paper a simple model for the evolution of the forward density of the future value of an asset is proposed. The model allows for a straightforward initial calibration to option prices and has dynamics that are consistent with…

Pricing of Securities · Quantitative Finance 2013-01-22 Henrik Hult , Filip Lindskog , Johan Nykvist

Fractional Brownian motion has become a standard tool to address long-range dependence in financial time series. However, a constant memory parameter is too restrictive to address different market conditions. Here we model the price…

Mathematical Finance · Quantitative Finance 2024-07-31 Axel A. Araneda

In this paper, we propose an iterative splitting method to solve the partial differential equations in option pricing problems. We focus on the Heston stochastic volatility model and the derived two-dimensional partial differential equation…

Computational Engineering, Finance, and Science · Computer Science 2020-03-31 Hongshan Li , Zhongyi Huang

We develop a novel deep learning approach for pricing European options in diffusion models, that can efficiently handle high-dimensional problems resulting from Markovian approximations of rough volatility models. The option pricing partial…

Computational Finance · Quantitative Finance 2025-04-04 Antonis Papapantoleon , Jasper Rou

We discuss various analytic and numerical methods that have been used to get option prices within a framework of the VG model. We show that some popular methods, for instance, Carr-Madan's FFT method could blow up for certain values of the…

Physics and Society · Physics 2010-01-15 Andrey Itkin

We develop cointegration for multivariate continuous-time stochastic processes, both in finite and infinite dimension. Our definition and analysis are based on factor processes and operators mapping to the space of prices and cointegration.…

Probability · Mathematics 2017-10-27 Fred Espen Benth , Andre Suess

In this paper, we present a novel approach to solving the American put options pricing model by hugely relying on a front-fixing Crank-Nicolson finite difference method. Since the American put option pricing model is a widely used financial…

Analysis of PDEs · Mathematics 2025-12-09 Z. I. Ali , M. A. Abebe

In this study, we propose a new formula for spread option pricing with the dependence of two assets described by a copula function. The advantage of the proposed method is that it requires only the numerical evaluation of a one-dimensional…

Pricing of Securities · Quantitative Finance 2023-08-31 Edoardo Berton , Lorenzo Mercuri

We obtain option pricing formulas for stock price models in which the drift and volatility terms are functionals of a continuous history of the stock prices. That is, the stock dynamics follows a nonlinear stochastic functional differential…

Pricing of Securities · Quantitative Finance 2020-11-17 Flavia Sancier , Salah Mohammed

Stochastic volatility (SV) and local stochastic volatility (LSV) processes can be used to model the evolution of various financial variables such as FX rates, stock prices, and so on. Considerable efforts have been devoted to pricing…

Computational Finance · Quantitative Finance 2013-12-20 Alexander Lipton , Andrey Gal , Andris Lasis

Non-equilibrium phenomena occur not only in physical world, but also in finance. In this work, stochastic relaxational dynamics (together with path integrals) is applied to option pricing theory. A recently proposed model (by Ilinski et…

Statistical Mechanics · Physics 2009-10-31 Matthias Otto

In this paper we study the pricing of exchange options when underlying assets have stochastic volatility and stochastic correlation. An approximation using a closed-form approximation based on a Taylor expansion of the conditional price is…

Pricing of Securities · Quantitative Finance 2020-01-14 Enrique Villamor , Pablo Olivares

This study focuses on the application of the Heston model to option pricing, employing both theoretical derivations and empirical validations. The Heston model, known for its ability to incorporate stochastic volatility, is derived and…

Computational Finance · Quantitative Finance 2024-10-22 Zheng Cao , Xinhao Lin

Diffusion processes driven by Fractional Brownian motion (FBM) have often been considered in modeling stock price dynamics in order to capture the long range dependence of stock price observed in reality. Option prices for such models had…

Statistics Theory · Mathematics 2024-05-29 Ananya Lahiri , Rituparna Sen

This study develops an integrated stochastic modeling framework for pricing short and medium-maturity equity options and assessing interest-rate risk using the Heston (1993), Bates (1996), and CIR (1985) models. We calibrate the Heston…

Portfolio Management · Quantitative Finance 2026-05-28 Nunik Srikandi Putri , Ajay Kumar Verma , Neo Paul Lesupi

This paper focuses on the pricing of the variance swap in an incomplete market where the stochastic interest rate and the price of the stock are respectively driven by Cox-Ingersoll-Ross model and Heston model with simultaneous L\'{e}vy…

Pricing of Securities · Quantitative Finance 2018-03-15 Ben-zhang Yang , Jia Yue , Nan-jing Huang

In this paper we present a simple, but new, approximation methodology for pricing a call option in a Black \& Scholes market characterized by stochastic interest rates. The method, based on a straightforward Gaussian moment matching…

Computational Finance · Quantitative Finance 2020-05-29 Fabio Antonelli , Alessandro Ramponi , Sergio Scarlatti