The stockyPuck project contains mathematical models for use with Zipline.io.

This project was developed as part of the CUNY Master of Science Data Analytics program's Mathematical Modeling course by Daniel Dittenhafer and Justin Hink.

Several trading algorithms were implemented in Python using Zipline.io framework for back testing to gauge performance.

• Fourier Transform: Using the SciPy FFT function and related helper functions to smooth and predict a security's price tomororw.

• Monte Carlo Simulation: Using NumPy statistics functions and the normal distribution to predict tomorrow's price.

An overview of the project and results can be found in the presentation slides or through our presentation video on YouTube.