collinc97 / stocksherlock

StockSherlock

A wise man once said: "It's elementary my dear Watson!" The same thing can be said about stock trade and comparison. Stock Sherlock uses the NASDAQ Data On Demand API to process EndOfDayData.xml files and convert them into monthly data snapshots in the form of numpy arrays that are modeled under our metrics: Variability Mean, Growth Rate, Volume Mean, Volume Spread, and Risk. This data is condensed and converted into a .csv file that IBM Watson's Tradeoff Analytics API displays in a stock comparison visualization tool.

Dependencies

The following pip packages must be installed for the backend to function properly.

• Flask
• Requests
• io
• pandas

Stock Comparison Quickstart

Instant Demo Here: http://stocksherlock.mybluemix.net/ (Don't worry there's a built in optional tutorial:)

Basic Overview:

1. Select up to 5 metrics and customize based on maximum or minimum.
2. Click HELP ME DECIDE in the lower right corner.
3. Narrow your stock options by adjusting the sliders on the left to refine your preferred metric results.
4. Add your top candidates on the right hand column to the final comparison.
5. Click COMPARE in the lower right corner.
6. Compare your final candidates by adding them to the final comparison on the right.
7. Make an informed financial decision based off NASDAQ Data On Demand and IBM Watson Tradeoff Analytics!

How to retrieve a .csv data file for a preferred month

1. Run runserver.py in /stocksherlock/stockBrowser/runserver.py
2. Navigate to localhost:5000/home in your browser
3. Select stocks to be filtered by NASDAQ API.
4. Select and submit date range.
5. Give IBM Watson your finaloutput.csv file produced by stockBrowser http://tradeoff-analytics-csvtojson.mybluemix.net/
6. Run the StockSherlock comparison tool!