A model for stocks dynamics based on a non-Gaussian path integral

TL;DR

This paper proposes a novel stock price dynamics model using a non-Gaussian path integral approach, generalizing previous models with tunable parameters to better fit stock and index fluctuations.

Contribution

It introduces a flexible, parameter-efficient model based on a non-quadratic path integral, extending Ilinski's approach for improved financial data fitting.

Findings

Accurately fits stock and index fluctuations

Uses a small number of parameters

Generalizes existing path integral models

Abstract

We introduce a model for the dynamics of stock prices based on a non quadratic path integral. The model is a generalization of Ilinski's path integral model, more precisely we choose a different action, which can be tuned to different time scales. The result is a model with a very small number of parameters that provides very good fits of some stock prices and indices fluctuations.