Option Pricing

This repository includes solving Option Pricing Models using Vanilla Python, minimizing the use of external libraries.

TODO

1. Filtering and Caliberation :: DONE
2. Full Caliberation Testing :: DONE
3. Penalty based Optimization
4. Feller Condition implementation :: Done, testing
5. Lewis' "Well Behaved Option Valuation"
6. Time Based Caliberation :: Not worth it
7. Gaussian Regression model :: Need to read
8. Julia Backend for Heston Function and PINNs :: DONE FOR HESTON
9. Adding new piece-wise optimization scheme

Tasks Completed

1. Black-Scholes Numerical
2. Black-Scholes Analytical
3. Black Scholes full testing(Results are good!)
4. Heston semi-Analytical
5. Heston semi-Analytical Testing
6. Heston Implementation
7. Heston Caliberation
8. Heston semi-Analytical
9. Heston semi-Analytical Testing
10. Heston Optimization with Gradient Descent
11. Setup the AAPL Dataset
12. Optimization Setup

Issues

1. Caliberation taking the right path, but weights need to be tuned