Difference between revisions of "Stock Analysis"
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== Project Overview == | == Project Overview == | ||
| − | + | The financial market is an extremely complicated place. While there are many metrics used to measure the health of markets, the S&P 500 is one which is universally valued. There are a number of factors that affect the S&P 500, and if one is able to accurately affect how a change in one of these factors, say the unemployment level, then you would be able to make better investment desicions. In order to enable this type of prediction, we will analyze various factors which might affect the S&P 500, construct a model of their behavior, and ultimately produce a graphical user interface so that a user can input their assumptions for a certain factor, and then receive the models predicted value of the S&P 500. | |
===Group Members=== | ===Group Members=== | ||
Revision as of 16:51, 18 September 2018
Project Overview
The financial market is an extremely complicated place. While there are many metrics used to measure the health of markets, the S&P 500 is one which is universally valued. There are a number of factors that affect the S&P 500, and if one is able to accurately affect how a change in one of these factors, say the unemployment level, then you would be able to make better investment desicions. In order to enable this type of prediction, we will analyze various factors which might affect the S&P 500, construct a model of their behavior, and ultimately produce a graphical user interface so that a user can input their assumptions for a certain factor, and then receive the models predicted value of the S&P 500.
Group Members
- Brandt Lawson
- Keith Kamons
- Jessica
Objectives
To produce a user interface which, given a user specified value for some factor, can predict what affect this value will have on future index values such as the s&p 500.
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.
Link to Project Log: Real Estate Log
