Predicting Tesla stock prices with RNNs

This is the code implementation of paper on unit root test with high frequency data. I will take TSLA as an example, to detect the bubble in it's stock price.

Install

    Supported Python version

         - Python version used in this project: 3.5+

    Libraries used

• Pandas 1.1.0
• Numpy 1.18.5
• Matplotlib 3.2.2
• seaborn 0.11.1
• scipy 1.5.0
• statsmodels0.11.1

Code