A comprehensive financial derivatives analysis application built with Python and Streamlit, developed for the Introductory Options Hackathon conducted by the Indian Institute of Technology (IIT), Guwahati.
This project demonstrates Black–Scholes option pricing, Greeks calculations, and risk assessment using real NVIDIA (NVDA) stock option data.
- 10 Comprehensive Tabs covering complete option pricing theory and practice
- Real-time Market Data from Yahoo Finance (12 months historical NVDA data)
- Interactive Simulator to experiment with option pricing parameters
- Educational explanations with formulas and real-world intuition
- Overview – Introduction to derivatives and options
- Market Data – Live NVDA data with candlestick charts and moving averages
- Volatility Analysis – Historical volatility and return distribution
- Black–Scholes Pricing – Call & Put pricing with P/L visualization
- Greeks – Delta, Theta, Vega with visual interpretation
- Risk & Hedging – Monte Carlo simulation and delta hedging
- Sensitivity Analysis – Impact of volatility and time to expiry
- Call vs Put – Comparison using payoff diagrams and parity
- Model Limitations – Real-world constraints and assumptions
- Interactive Simulator – Live parameter tuning with instant outputs
- Clean and professional UI
- Horizontal scrolling tabs
- Interactive Plotly charts
- Real-time calculations
- Beginner-friendly explanations
- Python 3.8+
- pip
git clone https://github.com/aishwanth-dev/NVDA-Option-Pricing-Risk-Analysis.git
cd NVDA-Option-Pricing-Risk-Analysis