Ill Posed Black-Scholes-Merton Equation Solver

Setup

Clone the prod branch repository: https://github.com/kss39/IllPosedBlackScholesEquation, and then at the repository root folder, run pip install .

Now you have a Python module called ipbse ready to import. The ipbse.predict file contains the most useful function: predict(). To use it, just do from ipbse import predict as ip.

(Note: It is recommended to use environment managers like virtualenv or conda.)

Run a demo

Run python demo.py. This Python script calculates a single "data block" - three consecutive trading days and predict the option price for the upcoming two days. The data here is synthetic (not real market data).

Example of processing a folder containing csv files

example.py contains the code below. It will fetch all csv files in the folder and process then sequentially. There is a test_data.csv in the folder for test use.

from pathlib import Path
from glob import glob
from ipbse import predict as ip

if __name__ == '__main__':
    for file in glob('*.csv'):
        filename = Path(file)
        print(f'Processing file {file}:')
        ip.predict(file, cpu_count=4).to_csv(f'{filename.parents[0]}/{filename.stem}_prediction.csv', index=False)