A Python practice project exploring Monte Carlo simulation techniques and their applications.
This repository contains implementations of various Monte Carlo simulations—a statistical method for modeling and analyzing systems with random variables. The project demonstrates the power of using statistical sampling to solve complex problems and estimate quantities that are difficult to calculate analytically.
- Monte Carlo Simulation
- Python
- Matplotlib (Data Visualization)
This project includes various simulation models with visual outputs to help understand Monte Carlo methods in action.
- Implementations of Monte Carlo simulation techniques
- Data visualization using Matplotlib
- Educational examples and demonstrations
- Active development and issue tracking
To explore this project:
-
Clone the repository:
git clone https://github.com/Pachrijam/Monte-Carlo-Simulation.git cd Monte-Carlo-Simulation -
Install required dependencies:
pip install matplotlib
-
Run simulation scripts to see Monte Carlo methods in action
The following features and enhancements are planned or under development:
- European Option Pricing via Monte Carlo: Implementation of risk-neutral Monte Carlo pricing for European calls and puts under the Black–Scholes framework with variance reduction techniques (antithetic variates, control variates)
- Validation against closed-form Black–Scholes prices
- Comprehensive unit tests and documentation
- Educational notebooks demonstrating variance reduction benefits
This is an active learning project. Contributions, suggestions, and improvements are welcome! Check the Issues page to see what's being worked on.
This project is open source and available on GitHub.
For more information on Monte Carlo methods, consider exploring:
- Monte Carlo integration techniques
- Probability and statistics concepts
- Numerical methods in Python