quantgirluk/aleatory
📦 Python library for Stochastic Processes Simulation and Visualisation
This tool helps financial analysts, quantitative researchers, and risk managers understand how different variables might evolve over time. It takes your chosen stochastic process (like Geometric Brownian Motion for stock prices) and generates multiple possible future paths, providing a clear visual representation of their behavior. You can use it to explore various scenarios and better comprehend the inherent uncertainty in your models.
357 stars. Available on PyPI.
Use this if you need to simulate and visualize the future behavior of financial instruments, economic indicators, or other random processes to test models or assess risk.
Not ideal if you are looking for a tool to perform real-time trading, complex portfolio optimization, or require advanced statistical inference beyond simulation and visualization.
Stars
357
Forks
39
Language
Python
License
MIT
Category
Last pushed
Mar 10, 2026
Commits (30d)
0
Dependencies
6
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