real-time predictive options model - mathematical modeling
Last updated Aug 30, 2024
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optionsrealtimemodeling
Numerical Solutions: Projects in Mathematical ModelingJaisal Friedman
Abstract
This paper explores the Black-Scholes-Merton options pricing model, derives a predictive extension model, and visualizes both models in comparison to real-time pricing options pricing. The paper also explores various methodologies of calculating historical volatility. A portfolio of 5 U.S. Market Stocks and 1 index fund was taken as example for the project. The model was limited to visual analysis from real-time simulations as further explained in the extensionsOverview
The project was written in python. The Jupyter notebook is a reference of how to interact with theoption_.py and pytradier.py files.
To configure the Library to run, rename the config_example.json file as config.json and enter your own details. You will need to get the required API keys, as well as install the python dependencies.
A sample of the generated 3D volatility surfaces is shown below.
Interactive Volatility Surfaces
Math
Please reference the paper/latex file in the GitHub for specifics on the Math behind each model.Extensions & Contact
There's some really interesting extensions, if you'd like to discuss please feel free to reach out to me :)Sample Renderings
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