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This paper proposes to model asset price dynamics with a mixture of diffusion processes where the instantaneous volatility of the underlying diffusion process contains a random vector. The marginal probability distributions of the proposed…

Mathematical Finance · Quantitative Finance 2018-09-20 Xin Liu

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

We show that the cost of market orders and the profit of infinitesimal market-making or -taking strategies can be expressed in terms of directly observable quantities, namely the spread and the lag-dependent impact function. Imposing that…

Data Analysis, Statistics and Probability · Physics 2008-12-02 Matthieu Wyart , Jean-Philippe Bouchaud , Julien Kockelkoren , Marc Potters , Michele Vettorazzo

Volatility prediction--an essential concept in financial markets--has recently been addressed using sentiment analysis methods. We investigate the sentiment of annual disclosures of companies in stock markets to forecast volatility. We…

Information Retrieval · Computer Science 2018-04-05 Navid Rekabsaz , Mihai Lupu , Artem Baklanov , Allan Hanbury , Alexander Duer , Linda Anderson

We propose a method to bound the expectation of the supremum of the price process in stochastic volatility models. It can be applied, for example, to the rough Bergomi model, avoiding the need to discuss finiteness of higher moments. Our…

Probability · Mathematics 2026-03-20 Stefan Gerhold , Julian Pachschwöll , Johannes Ruf

In this paper we develop numerical pricing methodologies for European style Exchange Options written on a pair of correlated assets, in a market with finite liquidity. In contrast to the standard multi-asset Black-Scholes framework, trading…

Pricing of Securities · Quantitative Finance 2020-06-16 Kevin S. Zhang , Traian A. Pirvu

Jumps and market microstructure noise are stylized features of high-frequency financial data. It is well known that they introduce bias in the estimation of volatility (including integrated and spot volatilities) of assets, and many methods…

Econometrics · Economics 2023-02-20 Qiang Liu , Zhi Liu

First, we show that implied normal volatility is intimately linked with the incomplete Gamma function. Then, we deduce an expansion on implied normal volatility in terms of the time-value of a European call option. Then, we formulate an…

Pricing of Securities · Quantitative Finance 2011-12-09 Cyril Grunspan

In this paper, we solve the multiple product price optimization problem under interval uncertainties of the price sensitivity parameters in the demand function. The objective of the price optimization problem is to maximize the overall…

Optimization and Control · Mathematics 2021-07-01 Mahdi Hamzeei , Alvin Lim , Jiefeng Xu

The present paper proposes a new framework for describing the stock price dynamics. In the traditional geometric Brownian motion model and its variants, volatility plays a vital role. The modern studies of asset pricing expand around…

Mathematical Finance · Quantitative Finance 2022-10-12 Ben Duan , Yutian Li , Dawei Lu , Yang Lu , Ran Zhang

In the first quarter of 2006 Chicago Board Options Exchange (CBOE) introduced, as one of the listed products, options on its implied volatility index (VIX). This created the challenge of developing a pricing framework that can…

Pricing of Securities · Quantitative Finance 2009-05-14 Claudio Albanese , Harry Lo , Aleksandar Mijatović

We study the price dynamics of 65 stocks from the Dow Jones Composite Average from 1973 until 2014. We show that it is possible to define a Daily Market Volatility $\sigma(t)$ which is directly observable from data. This quantity is usually…

Statistical Finance · Quantitative Finance 2015-03-30 Filippo Petroni , Maurizio Serva

The paper builds a Variance-Gamma (VG) model with five parameters: location ($\mu$), symmetry ($\delta$), volatility ($\sigma$), shape ($\alpha$), and scale ($\theta$); and studies its application to the pricing of European options. The…

Pricing of Securities · Quantitative Finance 2023-01-18 A. H. Nzokem

Most models for barrier pricing are designed to let a market maker tune the model-implied covariance between moves in the asset spot price and moves in the implied volatility skew. This is often implemented with a local…

Pricing of Securities · Quantitative Finance 2014-04-16 Mark Higgins

We consider a stochastic volatility model where the dynamics of the volatility are given by a possibly infinite linear combination of the elements of the time extended signature of a Brownian motion. First, we show that the model is…

Pricing of Securities · Quantitative Finance 2025-06-03 Eduardo Abi Jaber , Louis-Amand Gérard

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

It has been recently shown that spot volatilities can be very well modeled by rough stochastic volatility type dynamics. In such models, the log-volatility follows a fractional Brownian motion with Hurst parameter smaller than 1/2. This…

Statistical Finance · Quantitative Finance 2017-02-10 Giulia Livieri , Saad Mouti , Andrea Pallavicini , Mathieu Rosenbaum

We show that the frequent claim that the implied tree prices exotic options consistently with the market is untrue if the local volatilities are subject to change and the market is arbitrage-free. In the process, we analyse -- in the most…

Statistical Mechanics · Physics 2008-12-10 Karl Strobl

We establish an explicit approximation formula for European put option prices within a general stochastic volatility model with time-dependent parameters. Our methodology is based on expansions of the mixing representation of the put option…

Mathematical Finance · Quantitative Finance 2025-11-07 Kaustav Das , Nicolas Langrené

Generating realistic synthetic option prices requires implied volatility as an input, yet implied volatility is itself derived from observed option prices, creating a circular dependency that limits synthetic data for machine-learning and…

Computational Finance · Quantitative Finance 2026-05-15 Julia Sun , Zheyu Jin , Jiawei Zhang , Jeffrey D. Varner