tucker777/QSTK — pull request #4 by jpdus (2012-11-22 12:22:37+00:00)
Title: Added Quantquote data

Added support for free high quality daily S&P500 data from Quantquote to Data.Access.py .

Original Thread at Coursera CI Forums:
https://class.coursera.org/compinvesting1-2012-001/forum/thread?thread_id=4999

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After trying out QSTK and building some indicators etc. i quickly noticed that the Yahoo data is nice to try some features out but not reliable enough to build strategies on it - there are many gaps, unfiltered spikes and simply wrong prices in it.

After some searching on the web I found Quantquote - they provide high quality daily S&P500 data for free! (The only caveat is that it´s only updated quarterly - however for backtesting the data is just fine).

The Quantquote data comes fully adjusted (but with all adjustments fully documented) and additionally includes "earnings days" which is valuable for backtesting reasons, because stocks often behave differently on these days.

How to get the data into QSTK

Get the Quantquote data here ( https://quantquote.com/historical-stock-data - Free Data) and place the .csv files into /QSTK/QUSData/Quantquote .
Change DataAccess.py in /QSTK/qstkutil to the new version (you can just copy+paste the whole file).
Additional remarks

Use via DataAccess('Quantquote')
Available data columns: open, high, low, close, volume, splits, earnings, dividends
Please note: actual_close is available too but identical to close (because the whole data is adjusted already), i kept it in to make switching between Yahoo and Quantquote data easier and consistent.
You can find detailed information on the adjustment and earnings data (and how to deadjust) here ( https://quantquote.com/docs/QuantQuote_Minute.pdf ).