aleatory

Aleatory (/ˈeɪliətəri/) is a Python library for simulating and visualising stochastic processes defined by Stochastic Differential Equations (SDEs). It introduces objects representing continuous-time stochastic processes \(X = \{X_t : t\geq 0\}\), and provides functionality to:

• generate realizations/trajectories of each process over discrete time sets

• create visualisations to illustrate the processes properties and behaviour

Currently, aleatory supports the following processes:

• Brownian Motion

• Geometric Brownian Motion

• Ornstein–Uhlenbeck

• Vasicek

• Cox–Ingersoll–Ross

• Constant Elasticity

Installation

Aleatory is available on pypi and can be installed as follows

pip install aleatory

Dependencies

Aleatory relies heavily on

• numpy scipy for random number generation, as well as support for a number of one-dimensional distributions.

• matplotlib for creating visualisations

Compatibility

Aleatory is tested on Python versions 3.8, 3.9, and 3.10.

Documentation

• Quick-Start Guide
  • The simulate() method
  • The plot() method
  • The draw() method
  • Charts Customisation
• Analytical Processes
  • BrownianMotion
  • GBM
• EM Processes
  • OUProcess
  • Vasicek
  • CIRProcess
  • CEVProcess

Indices and tables

• Index

• Search Page