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In this paper, we obtain sharp asymptotic formulas with error estimates for the Mellin convolution of functions, and use these formulas to characterize the asymptotic behavior of marginal distribution densities of stock price processes in…

Pricing of Securities · Quantitative Finance 2014-03-24 Archil Gulisashvili , Josep Vives

We model the stock price dynamics through a semi-Markov process obtained using a Poisson random measure. We establish the existence and uniqueness of the classical solution of a non-homogeneous terminal value problem and we show that the…

Mathematical Finance · Quantitative Finance 2022-09-13 Garima Agrawal , Anindya Goswami

Using machine learning and alternative data for the prediction of financial markets has been a popular topic in recent years. Many financial variables such as stock price, historical volatility and trade volume have already been through…

Computational Finance · Quantitative Finance 2020-09-18 Thomas Dierckx , Jesse Davis , Wim Schoutens

We present a new microscopic stochastic model for an ensemble of interacting investors that buy and sell stocks in discrete time steps via limit orders based on individual forecasts about the price of the stock. These orders determine the…

Statistical Mechanics · Physics 2015-06-25 C. Busshaus , H. Rieger

Financial markets are an intriguing place that offer investors the potential to gain large profits if timed correctly. Unfortunately, the dynamic, non-linear nature of financial markets makes it extremely hard to predict future price…

Machine Learning · Computer Science 2023-05-09 Daniel Boyle , Jugal Kalita

Trade prices of about 1000 New York Stock Exchange-listed stocks are studied at one-minute time resolution over the continuous five year period 2018--2022. For each stock, in dollar-volume-weighted transaction time, the discrepancy from a…

Pricing of Securities · Quantitative Finance 2023-05-16 William H. Press

Recent studies have identified long-range dependence as a key feature in the dynamics of both mortality and interest rates. Building on this insight, we develop a novel bi-variate stochastic framework based on mixed fractional Brownian…

Risk Management · Quantitative Finance 2025-08-26 Kenneth Q. Zhou , Hongjuan Zhou

In this paper, we consider the drawdown and drawup of the fractional Brownian motion with trend, which corresponds to the logarithm of geometric fractional Brownian motion representing the stock price in financial market. We derive the…

Probability · Mathematics 2018-02-01 Long Bai , Peng Liu

Classical technical analysis methods of stock evolution are recalled, i.e. the notion of moving averages and momentum indicators. The moving averages lead to define death and gold crosses, resistance and support lines. Momentum indicators…

Condensed Matter · Physics 2009-11-07 M. Ausloos , K. Ivanova

Contrary to the common view that exact pricing is prohibitive owing to the curse of dimensionality, this study proposes an efficient and unified method for pricing options under multivariate Black-Scholes-Merton (BSM) models, such as the…

Pricing of Securities · Quantitative Finance 2018-05-09 Jaehyuk Choi

The authors aim to develop numerical schemes of the two representative quadratic hedging strategies: locally risk minimizing and mean-variance hedging strategies, for models whose asset price process is given by the exponential of a normal…

Computational Finance · Quantitative Finance 2018-01-18 Takuji Arai , Yuto Imai , Ryo Nakashima

The Generalized fractional Brownian motion (gfBm) is a stochastic process that acts as a generalization for both fractional, sub-fractional, and standard Brownian motion. Here we study its use as the main driver for price fluctuations,…

Mathematical Finance · Quantitative Finance 2023-11-14 Axel A. Araneda

The principle of absence of arbitrage opportunities allows obtaining the distribution of stock price fluctuations by maximizing its information entropy. This leads to a physical description of the underlying dynamics as a random walk…

Statistical Finance · Quantitative Finance 2013-10-31 Rosario Bartiromo

We obtain a decomposition of the call option price for a very general stochastic volatility diffusion model extending the decomposition obtained by E. Al\`os in [2] for the Heston model. We realize that a new term arises when the stock…

Mathematical Finance · Quantitative Finance 2015-03-30 Raul Merino , Josep Vives

The paper presents a step forward into the development of the theory of meaning. Stock and financial markets are examined from communication-theoretical perspective on the dynamics of information and meaning. This study focuses on the link…

Statistical Finance · Quantitative Finance 2023-12-19 Inga Ivanova

One the one hand, rough volatility has been shown to provide a consistent framework to capture the properties of stock price dynamics both under the historical measure and for pricing purposes. On the other hand, market price of volatility…

Mathematical Finance · Quantitative Finance 2025-12-05 Ofelia Bonesini , Antoine Jacquier , Aitor Muguruza

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

We propose a method for extending a given asset pricing formula to account for two additional sources of risk: the risk associated with future changes in market--calibrated parameters and the remaining risk associated with idiosyncratic…

Disordered Systems and Neural Networks · Physics 2008-12-02 T. R. Hurd

We design an optimal strategy for investment in a portfolio of assets subject to a multiplicative Brownian motion. The strategy provides the maximal typical long-term growth rate of investor's capital. We determine the optimal fraction of…

Statistical Mechanics · Physics 2008-12-02 Sergei Maslov , Yi-Cheng Zhang

The purpose of this work is to explore the role that random arbitrage opportunities play in pricing financial derivatives. We use a non-equilibrium model to set up a stochastic portfolio, and for the random arbitrage return, we choose a…

Other Condensed Matter · Physics 2008-12-10 Sergei Fedotov , Stephanos Panayides