Recent Stock Market Analysis

There have been two major downturns in the stock market since January of 2020. This project will create and train a model that will look for key factors in each downturn and answer the following questions.

1. Which sectors of the stock market were affected the most during the downturns?  
2. Which sectors of the stock market were affected the least during the downturns? 
3. Can we build a model that predicts future stock prices?

The two timeframes that will be analyzed are January 1st, 2020 - March 31st, 2021 and April 1st, 2021 to present day. Click here to view our project dashboard and final results.

Reason for selecting this topic

A vast amount of information is available regarding all facets of the stock market. In order to create and train a successful model, access to meaningful data is extremely important.

The collaborators of this project share an interest and curiosity about all things as they relate to the stock market. This interest combined with the available data lead to the selection of this project.

Presentation

Click here for a link to the Google Slides presentation.

Data Selection and ETL

- Data Extraction
- Data Transformation
- Data Storage - Postgres/AWS RDS

Database Connection, Retrieval, and Machine Learning

Amazon AWS and PostgreSQL were used for the database during this project. To view the final code and machine learning models, please click here

Machine Learning Models

1. Stock Sector Comparison
   • Create supervised learning model (logistic regression)
   • Train
   • Predict (classification)
   • Validate (accuracy)

Correlation Plot - All Companies