Monte-Carlo-Option-Pricing-Simulator

A Python simulator that prices European calls and puts with Monte Carlo methods, simulates paths with geometric Brownian motion, and compares against Black-Scholes.

This is a professional simulator for pricing European Call and Put options with Monte Carlo methods, built in Python under the MIT license. It simulates stock price paths using Geometric Brownian Motion, prices the options by simulation, then compares those prices against the Black-Scholes analytical values. Results come with animated plots. The README names its intended audience directly: finance, education, and research.

The feature list is compact. Simulate stock price paths with GBM, price European calls and puts via Monte Carlo, calculate the Black-Scholes analytical price, visualize animated price paths and option prices, and a clean, professional dark theme. There is no claim of real market data or live feeds anywhere in the README.

Four files make up the project. main.py is the entry point, handling simulation, visualization, and the comparison. utils.py holds the GBM simulation and pricing functions. requirements.txt lists Python dependencies, and README.md carries the documentation and formulas. It is a deliberately small structure for a focused tool.

The README prints the formulas in full. Stock price evolution follows geometric Brownian motion, with the price at time t, the initial price, the risk-free rate, volatility, and a Wiener process as the moving parts. Black-Scholes appears for both directions: the European call and the European put, with d1 and d2 defined, a strike price, time to maturity, and the cumulative distribution function of the standard normal distribution. Everything a reader needs to check the implementation is written down.

The value here is transparency. The formulas, the file layout, and the feature set are all on the page, so the simulator can be checked against the math it claims to implement.

• Source 1 · Project repository
• Source 2 · README