A personal project featuring a suite of classes, functions, and scripts designed to showcase the implementation and application of stochastic processes in a finance and investment context. By incorporating Monte Carlo techniques alongside Brownian motion, square-root diffusion, and Ornstein–Uhlenbeck models, this package provides:
- Path generation and simulation for a variety of financial instruments, aimed at pricing and risk analysis.
- Scenario testing and sensitivity analyses, leveraging advanced models to capture market volatility and mean-reversion behaviors.
- Flexible codebase for easy integration into broader quantitative strategies, including portfolio optimization and derivatives pricing.
This repository underscores a hands-on approach to quantitative finance—demonstrating how robust stochastic methods can help model, forecast, and manage uncertainty in real-world investment environments.