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In the classical model of stock prices which is assumed to be Geometric Brownian motion, the drift and the volatility of the prices are held constant. However, in reality, the volatility does vary. In quantitative finance, the Heston model…

Pricing of Securities · Quantitative Finance 2019-10-21 Arunangshu Biswas , Anindya Goswami , Ludger Overbeck

An efficient compression technique based on hierarchical tensors for popular option pricing methods is presented. It is shown that the "curse of dimensionality" can be alleviated for the computation of Bermudan option prices with the Monte…

Computational Finance · Quantitative Finance 2021-03-09 Christian Bayer , Martin Eigel , Leon Sallandt , Philipp Trunschke

First, classes of Markov processes that scale exactly with a Hurst exponent H are derived in closed form. A special case of one class is the Tsallis density, advertised elsewhere as nonlinear diffusion or diffusion with nonlinear feedback.…

Physics and Society · Physics 2008-12-02 J. L. McCauley , G. H. Gunaratne , K. E. Bassler

We consider the Black--Scholes model of financial market modified to capture the stochastic nature of volatility observed at real financial markets. For volatility driven by the Ornstein--Uhlenbeck process, we establish the existence of…

Pricing of Securities · Quantitative Finance 2015-10-08 Sergii Kuchuk-Iatsenko , Yuliya Mishura

It is well known that the Black-Scholes-Merton model suffers from several deficiencies. Jump-diffusion and Levy models have been widely used to partially alleviate some of the biases inherent in this classical model. Unfortunately, the…

Computational Engineering, Finance, and Science · Computer Science 2007-05-23 Kenneth R. Jackson , Sebastian Jaimungal , Vladimir Surkov

We present an approach for pricing European call options in presence of proportional transaction costs, when the stock price follows a general exponential L\'{e}vy process. The model is a generalization of the celebrated work of Davis,…

Mathematical Finance · Quantitative Finance 2021-06-18 Nicola Cantarutti , João Guerra , Manuel Guerra , Maria do Rosário Grossinho

A growing body of literature suggests that heavy tailed distributions represent an adequate model for the observations of log returns of stocks. Motivated by these findings, here we develop a discrete time framework for pricing of European…

Pricing of Securities · Quantitative Finance 2019-04-19 Lasko Basnarkov , Viktor Stojkoski , Zoran Utkovski , Ljupco Kocarev

We show that our generalization of the Black-Scholes partial differential equation (pde) for nontrivial diffusion coefficients is equivalent to a Martingale in the risk neutral discounted stock price. Previously, this was proven for the…

Physics and Society · Physics 2009-11-11 J. L. McCauley , G. H. Gunaratne , K. E. Bassler

Mathematically, the execution of an American-style financial derivative is commonly reduced to solving an optimal stopping problem. Breaking the general assumption that the knowledge of the holder is restricted to the price history of the…

Computational Finance · Quantitative Finance 2020-08-25 Bernardo D'Auria , Eduardo García-Portugués , Abel Guada

We consider plain vanilla European options written on an underlying asset that follows a continuous time semi-Markov multiplicative process. We derive a formula and a renewal type equation for the martingale option price. In the case in…

Probability · Mathematics 2021-08-06 Enrico Scalas , Bruno Toaldo

We consider the problem of pricing discretely monitored Asian options over $T$ monitoring points where the underlying asset is modeled by a geometric Brownian motion. We provide two quantum algorithms with complexity poly-logarithmic in $T$…

This paper provides evidence that stock returns, after truncation, might be modeled by a special type of continuous mixtures or normals, so-called $q$-Gaussians. Negative binomial distributions might model the counts for extreme returns. A…

Mathematical Finance · Quantitative Finance 2025-03-12 Xinxin Jiang

We present a simple, fast, and accurate method for pricing a variety of discretely monitored options in the Black-Scholes framework, including autocallable structured products, single and double barrier options, and Bermudan options. The…

Computational Finance · Quantitative Finance 2019-06-04 Min Huang , Guo Luo

In this short paper, in order to price occupation-time options, such as (double-barrier) step options and quantile options, we derive various joint distributions of a mixed-exponential jump-diffusion process and its occupation times of…

Probability · Mathematics 2016-03-31 Djilali Ait Aoudia , Jean-François Renaud

We study the behavior of the critical price of an American put option near maturity in the Jump diffusion model when the underlying stock pays dividends at a continuous rate and the limit of the critical price is smaller than the stock…

Probability · Mathematics 2014-06-26 Aych Bouselmi , Damien Lamberton

The aim of this chapter is to show how option prices in jump-diffusion models can be computed using meshless methods based on Radial Basis Function (RBF) interpolation. The RBF technique is demonstrated by solving the partial…

Computational Finance · Quantitative Finance 2011-10-26 Ron T. L. Chan , Simon Hubbert

In this research, we proposed a Mean Convection Finite Difference Method (MCFDM) for European options pricing. The Black-Scholes model, which describes the dynamics of a financial asset, was first transformed into a convection-diffusion…

Numerical Analysis · Mathematics 2023-08-15 An Ning

Here we develop an option pricing method based on Legendre series expansion of the density function. The key insight, relying on the close relation of the characteristic function with the series coefficients, allows to recover the density…

Mathematical Finance · Quantitative Finance 2017-03-21 Julien Hok , Tat Lung Chan

We propose a multi-scale stochastic volatility model in which a fast mean-reverting factor of volatility is built on top of the Heston stochastic volatility model. A singular pertubative expansion is then used to obtain an approximation for…

Pricing of Securities · Quantitative Finance 2012-05-15 Jean-Pierre Fouque , Matthew Lorig

We propose a novel structural estimation framework in which we train a surrogate of an economic model with deep neural networks. Our methodology alleviates the curse of dimensionality and speeds up the evaluation and parameter estimation by…

Econometrics · Economics 2021-02-19 Hui Chen , Antoine Didisheim , Simon Scheidegger