Difference between revisions of "Stock Analysis"
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Our goal is to exclusively use open source data and software, which makes our budget $0.00. | Our goal is to exclusively use open source data and software, which makes our budget $0.00. | ||
| − | + | ==Data== | |
| − | ==Data Scraping== | + | =====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. | 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== | + | =====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. | 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. | ||
Revision as of 17:24, 19 September 2018
Link to Project Log: Stock Analysis Log
Contents
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
- Chang Xue
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.
Challanges
- Learning how to use MySQL.
- Learning how to use Python's data analysis toolboxes.
- Data collection and storage in an efficient way
Gantt Chart
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.
