Sample code that shows how to forecast stock market volatility using a Kalman filter.
Created by Jin Choi, PhD https://www.eddywealth.com/about/jin-choi/
Install dependencies using pip::
pip install -r requirements.txt
If you have CUDA installed, you may want to install pytorch separately. Doing so will significantly speed up model training.
The following will automatically download the data, train the model, and generate charts comparing forecasts to actual.
python main.py
The code in this repository is intended for educational purposes only. Neither Jin nor the companies he works for is responsible for any losses arising from the use of this code.