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We investigate the statistical evidence for the use of `rough' fractional processes with Hurst exponent $H< 0.5$ for the modeling of volatility of financial assets, using a model-free approach. We introduce a non-parametric method for…

Statistical Finance · Quantitative Finance 2023-07-11 Rama Cont , Purba Das

We study a market model in which the volatility of the stock may jump at a random time from a fixed value to another fixed value. This model was already described in the literature. We present a new approach to the problem, based on partial…

Statistical Mechanics · Physics 2008-12-02 Miquel Montero

Options are financial instruments that depend on the underlying stock. We explain their non-Gaussian fluctuations using the nonextensive thermodynamics parameter $q$. A generalized form of the Black-Scholes (B-S) partial differential…

Statistical Mechanics · Physics 2009-11-07 Lisa Borland

This paper concerns a local volatility model in which volatility takes two possible values, and the specific value depends on whether the underlying price is above or below a given threshold value. The model is known, and a number of…

Mathematical Finance · Quantitative Finance 2024-05-17 Alexander Gairat , Vadim Shcherbakov

Volatility, as a primary indicator of financial risk, forms the foundation of classical frameworks such as Markowitz's Portfolio Theory and the Efficient Market Hypothesis (EMH). However, its conventional use rests on assumptions-most…

General Finance · Quantitative Finance 2025-08-19 Sergio Bianchi , Daniele Angelini , Massimiliano Frezza , Augusto Pianese

We consider stochastic differential equation involving pathwise integral with respect to fractional Brownian motion. The estimates for the Hurst parameter are constructed according to first- and second-order quadratic variations of observed…

Probability · Mathematics 2012-06-28 K. Kubilius , Y. Mishura

This paper deals with the identification of the multivariate fractional Brownian motion, a recently developed extension of the fractional Brownian motion to the multivariate case. This process is a $p$-multivariate self-similar Gaussian…

Statistics Theory · Mathematics 2011-11-16 Pierre-Olivier Amblard , Jean-François Coeurjolly

In this article we model a financial derivative price as an observable on the market state function. We apply geometric techniques to integrating the Heisenberg Equation of Motion. We illustrate how the non-commutative nature of the model…

Mathematical Finance · Quantitative Finance 2020-01-27 Will Hicks

The model describing market dynamics after a large financial crash is considered in terms of the stochastic differential equation of Ito. Physically, the model presents an overdamped Brownian particle moving in the nonstationary…

Statistical Finance · Quantitative Finance 2008-12-02 G. L. Buchbinder , K. M. Chistilin

In this paper, we introduce and analyze the fractional Barndorff-Nielsen and Shephard (BN-S) stochastic volatility model. The proposed model is based upon two desirable properties of the long-term variance process suggested by the empirical…

Mathematical Finance · Quantitative Finance 2022-01-26 Nicholas Salmon , Indranil SenGupta

We fit the volatility fluctuations of the S&P 500 index well by a Chi distribution, and the distribution of log-returns by a corresponding superposition of Gaussian distributions. The Fourier transform of this is, remarkably, of the Tsallis…

Pricing of Securities · Quantitative Finance 2009-06-16 Petr Jizba , Hagen Kleinert , Patrick Haener

Exponential functionals of Brownian motion have been extensively studied in financial and insurance mathematics due to their broad applications, for example, in the pricing of Asian options. The Black-Scholes model is appealing because of…

Pricing of Securities · Quantitative Finance 2016-10-04 Runhuan Feng , Alexey Kuznetsov , Fenghao Yang

In this paper, we study a class of one-dimensional stochastic differential equations driven by fractional Brownian motion with Hurst parameter $H>\ff 1 2$. The drift term of the equation is locally Lipschitz and unbounded in the…

Probability · Mathematics 2019-01-01 Shao-Qin Zhang , Chenggui Yuan

We investigated the quality of forecasting of fractional Brownian motion, and new method for estimating of Hurst exponent is validated. Stochastic model of the time series in the form of converted fractional Brownian motion is proposed. The…

Probability · Mathematics 2017-04-05 Valeria Bondarenko , Victor Bondarenko , Kiryl Truskovsky , Ina Taralova

There is vast empirical evidence that given a set of assumptions on the real-world dynamics of an asset, the European options on this asset are not efficiently priced in options markets, giving rise to arbitrage opportunities. We study…

Pricing of Securities · Quantitative Finance 2011-10-03 Rudra P. Jena , Peter Tankov

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

The paper suggests a way of stochastic integration of random integrands with respect to fractional Brownian motion with the Hurst parameter H> 1/2. The integral is defined initially on the processes that are "piecewise" predictable on a…

Probability · Mathematics 2020-04-21 Nikolai Dokuchaev

We consider stochastic differential equation $$ d X_t=b(X_t) dt +d W_t^H, $$ where the drift $b$ is either a measure or an integrable function, and $W^H$ is a $d$-dimensional fractional Brownian motion with Hurst parameter $H\in(0,1)$,…

Probability · Mathematics 2025-10-22 Oleg Butkovsky , Khoa Lê , Leonid Mytnik

We introduce fractional Brownian motion processes (fBm) as an alternative model for the turbulent index of refraction. These processes allow to reconstruct most of the index properties, but they are not differentiable. We overcome the…

Optics · Physics 2007-05-23 Dario G Perez

Many studies assume stock prices follow a random process known as geometric Brownian motion. Although approximately correct, this model fails to explain the frequent occurrence of extreme price movements, such as stock market crashes. Using…

Statistical Finance · Quantitative Finance 2015-05-14 Miguel A. Fuentes , Austin Gerig , Javier Vicente