Stock Analysis

Link to Project Log: Stock Analysis Log

Project Overview

The financial market is an extremely complicated place. While there are many metrics used to measure the health of markets, market values such as the S&P 500, Russell 2000, and the Dow Jones Industrial average are the ones that we will focus on. We will build models of the market so that users can input how they think the interest rate, unemployment rate, price of gold, and other factors will change, and our models will predict how the market will react to those changes. The user will enter their predictions into a user interface, and the product will output visual aid as well as estimated prices and behavior. Our product will help users make more informed investment decisions.

Group Members

• Brandt Lawson
• Keith Kamons
• Jessica
• Chang Xue (TA)

Objectives

Produce a user interface which, given a user specified value for some factors, can predict what impact this change will have on future index values. The accuracy and precision of the model can be determine through back testing and measure the success of the project. We will demonstrate our project by allowing users to predict changes in many factors and to see how our model does at predicting the markets reaction.

Challanges

• Learning how to use MySQL.
• Learning how to use Python's data analysis toolboxes.
  • Integrating this software across different platforms and allowing everyone in the group to have access to this data.
• Data collection and storage in an efficient and complete way

Budget

Our goal is to exclusively use open source data and software, which makes our budget $0.00.

Data

Data Scraping

In order to enable our data set to dynamically update, we must create code that will "scrape" the newest information from the specified website.

Database

Once this new data is scraped, we will add it to our relational database using SQL. This will make it more organized and easily searchable.