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We frame the issue of pedestrian dynamics modeling in terms of path-integrals, a formalism originally introduced in quantum mechanics to account for the behavior of quantum particles, later extended to quantum field theories and to…

Physics and Society · Physics 2020-11-04 Alessandro Corbetta , Federico Toschi

Stock prices are known to exhibit non-Gaussian dynamics, and there is much interest in understanding the origin of this behavior. Here, we present a model that explains the shape and scaling of the distribution of intraday stock price…

Statistical Finance · Quantitative Finance 2015-05-13 Austin Gerig , Javier Vicente , Miguel A. Fuentes

We present evidence that the best model for empirical volume-price distributions is not always the same and it strongly depends in (i) the region of the volume-price spectrum that one wants to model and (ii) the period in time that is being…

Statistical Finance · Quantitative Finance 2015-06-22 Paulo Rocha , Frank Raischel , João Pedro Boto , Pedro G. Lind

A discrete time probabilistic model, for optimal equity allocation and portfolio selection, is formulated so as to apply to (at least) reinsurance. In the context of a company with several portfolios (or subsidiaries), representing both…

Optimization and Control · Mathematics 2008-12-02 Erik Taflin

It is discussed an opportunity to introduce new class of quantum algorithms based on possibility to express amplitude of transition between two states of quantum system as sum of some function along all possible classical paths. Continuous…

Quantum Physics · Physics 2007-05-23 Alexander Yu. Vlasov

We propose a general interpretation for long-range correlation effects in the activity and volatility of financial markets. This interpretation is based on the fact that the choice between `active' and `inactive' strategies is subordinated…

Disordered Systems and Neural Networks · Physics 2009-11-07 Irene Giardina , Jean-Philippe Bouchaud , Marc Mézard

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

Quantum computers are expected to contribute more efficient and accurate ways of modeling economic processes. Quantum hardware is currently available at a relatively small scale, but effective algorithms are limited by the number of logic…

Quantum Physics · Physics 2024-01-18 Dominic Widdows , Amit Bhattacharyya

This study investigates enhancing option pricing by extending the Black-Scholes model to include stochastic volatility and interest rate variability within the Partial Differential Equation (PDE). The PDE is solved using the finite…

Numerical Analysis · Mathematics 2025-04-15 Nikhil Shivakumar Nayak

Local volatility is a versatile option pricing model due to its state dependent diffusion coefficient. Calibration is, however, non-trivial as it involves both proposing a hypothesis model of the latent function and a method for fitting it…

Mathematical Finance · Quantitative Finance 2021-12-08 Martin Tegner , Stephen Roberts

We discuss the time evolution of quotations of stocks and commodities and show that corrections to the orthodox Bachelier model inspired by quantum mechanical time evolution of particles may be important. Our analysis shows that traders…

Condensed Matter · Physics 2015-06-24 E. W. Piotrowski , J. Sladkowski

We propose a very efficient method for pricing various types of lookback options under Markov models. We utilize the model-free representations of lookback option prices as integrals of first passage probabilities. We combine efficient…

Computational Finance · Quantitative Finance 2021-12-02 Gongqiu Zhang , Lingfei Li

We apply the formalism of the continuous time random walk to the study of financial data. The entire distribution of prices can be obtained once two auxiliary densities are known. These are the probability densities for the pausing time…

Statistical Mechanics · Physics 2008-12-10 Jaume Masoliver , Miquel Montero , George H. Weiss

Even if path planning can be solved using standard techniques from dynamic programming and control, the problem can also be approached using probabilistic inference. The algorithms that emerge using the latter framework bear some appealing…

We formulate Bayesian updates in Markov processes by means of path integral techniques and derive the imaginary-time Schr\"{o}dinger equation with likelihood to direct the inference incorporated as a potential for the posterior probability…

Statistics Theory · Mathematics 2017-10-24 Toshiyuki Fujii , Noriyuki Hatakenaka

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 introduce a prototype model in an attempt to capture some aspects of market dynamics simulating a trading mechanism. The model description starts with a discrete-space, continuous-time Markov process describing arrival and movement of…

Trading and Market Microstructure · Quantitative Finance 2013-04-04 N. Vvedenskaya , Y. Suhov , V. Belitsky

Over the last decade, dividends have become a standalone asset class instead of a mere side product of an equity investment. We introduce a framework based on polynomial jump-diffusions to jointly price the term structures of dividends and…

Mathematical Finance · Quantitative Finance 2020-05-26 Damir Filipović , Sander Willems

The market weight of a stock is its capitalization (cap) divided by the total market cap. Rank these weights from top to bottom. The capital distribution curve is a plot of weights versus ranks. For the US stock market, it is linear on a…

Probability · Mathematics 2019-07-23 Clayton Barnes , Andrey Sarantsev

Path integrals represent a powerful route to quantization: they calculate probabilities by summing over classical configurations of variables such as fields, assigning each configuration a phase equal to the action of that configuration.…

Quantum Physics · Physics 2013-02-13 Seth Lloyd , Olaf Dreyer