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We use the expectation of the range of an arithmetic Brownian motion and the method of moments on the daily high, low, opening and closing prices to estimate the volatility of the stock price. The daily price jump at the opening is…

Statistical Finance · Quantitative Finance 2011-12-21 Cristin Buescu , Michael Taksar , Fatoumata J. Koné

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

Closed form option pricing formulae explaining skew and smile are obtained within a parsimonious non-Gaussian framework. We extend the non-Gaussian option pricing model of L. Borland (Quantitative Finance, {\bf 2}, 415-431, 2002) to include…

Other Condensed Matter · Physics 2009-09-29 L. Borland , J. P. Bouchaud

Motivated by the Corns-Satchell, continuous time, option pricing model, we develop a binary tree pricing model with underlying asset price dynamics following It\^o-Mckean skew Brownian motion. While the Corns-Satchell market model is…

Mathematical Finance · Quantitative Finance 2023-03-31 Yuan Hu , W. Brent Lindquist , Svetlozar T. Rachev , Frank J. Fabozzi

This paper considers the asset price p as relations C=pV between the value C and the volume V of the executed transactions and studies the consequences of this definition for the option pricing equations. We show that the classical BSM…

Pricing of Securities · Quantitative Finance 2021-02-24 Victor Olkhov

It was demonstrated previously that the stochastic volatility emerges as the gauge field necessary for restoring the local symmetry under changes of the prices of the stocks inside the Black-Scholes (BS) equation. When this occurs, then a…

Pricing of Securities · Quantitative Finance 2025-04-04 Ivan Arraut

In the present paper we present a finite element approach for option pricing in the framework of a well-known stochastic volatility model with jumps, the Bates model. In this model the asset log-returns are assumed to follow a…

Computational Finance · Quantitative Finance 2008-12-17 Edie Miglio , Carlo Sgarra

This paper develops a model that incorporates the presence of stochastic arbitrage explicitly in the Black--Scholes equation. Here, the arbitrage is generated by a stochastic bubble, which generalizes the deterministic arbitrage model…

Mathematical Finance · Quantitative Finance 2021-09-15 Mauricio Contreras G

In recent literature it is claimed that BitCoin price behaves more likely to a volatile stock asset than a currency and that changes in its price are influenced by sentiment about the BitCoin system itself; in Kristoufek [10] the author…

Mathematical Finance · Quantitative Finance 2019-09-23 Alessandra Cretarola , Gianna Figà-Talamanca , Marco Patacca

In a model with no given probability measure, we consider asset pricing in the presence of frictions and other imperfections and characterize the property of coherent pricing, a notion related to (but much weaker than) the no arbitrage…

Mathematical Finance · Quantitative Finance 2016-09-12 Gianluca Cassese

In a seminal paper in 1973, Black and Scholes argued how expected distributions of stock prices can be used to price options. Their model assumed a directed random motion for the returns and consequently a lognormal distribution of asset…

Computational Engineering, Finance, and Science · Computer Science 2009-11-07 Joseph L. McCauley , Gemunu H. Gunaratne

A new mathematical model for the Black-Scholes equation is proposed to forecast option prices. This model includes new interval for the price of the underlying stock as well as new initial and boundary conditions. Conventional notions of…

Mathematical Finance · Quantitative Finance 2015-03-13 Michael V. Klibanov , Andrey V. Kuzhuget

We derive the Black-Scholes-Merton dual equation, which has exactly the same form as the Black-Scholes-Merton equation. The novel and general equation works for options with a payoff of homogeneous of degree one, including European,…

Pricing of Securities · Quantitative Finance 2024-05-20 Shuxin Guo , Qiang Liu

Model risk measures consequences of choosing a model in a class of possible alternatives. We find analytical and simulated bounds for payoff functions on classes of plausible alternatives of a given discrete model. We measure the impact of…

Mathematical Finance · Quantitative Finance 2023-02-20 Roberto Fontana , Patrizia Semeraro

On April 22, 2020, the CME Group switched to Bachelier pricing for a group of oil futures options. The Bachelier model, or more generally the arithmetic Brownian motion (ABM), is not so widely used in finance, though. This paper provides…

Pricing of Securities · Quantitative Finance 2024-11-12 Qiang Liu , Shuxin Guo

Pricing of high-dimensional options is a deep problem of the Theoretical Financial Mathematics. In this article we present a new class of L\'{e}vy driven models of stock markets. In our opinion, any market model should be based on a…

Computational Finance · Quantitative Finance 2014-01-10 Alexander Kushpel

This work considers a stochastic model in which the uncertainty is driven by a multidimensional Brownian motion. The market price of risk process makes the transition between real world probability measure and risk neutral probability…

Probability · Mathematics 2017-10-04 Traian A. Pirvu , Ulrich G. Haussmann

The problem of hedging and pricing sequences of contingent claims in large financial markets is studied. Connection between asymptotic arbitrage and behavior of the $\alpha$~-~quantile price is shown. The large Black-Scholes model is…

Mathematical Finance · Quantitative Finance 2015-12-22 Michał Barski

Pricing of high-dimensional options is one of the most important problems in Mathematical Finance. The objective of this manuscript is to present an original self-contained treatment of the multidimensional pricing. During the past decades…

Mathematical Finance · Quantitative Finance 2015-10-27 Alexander Kushpel

This paper aims to provide a practical example on the assessment and propagation of input uncertainty for option pricing when using tree-based methods. Input uncertainty is propagated into output uncertainty, reflecting that option prices…

Computational Engineering, Finance, and Science · Computer Science 2007-05-23 Henryk Gzyl , German Molina , Enrique ter Horst