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I am using the yahoo finance python module: https://pypi.python.org/pypi/yahoo-finance

I am using it for a project and would like to see if anybody else uses data from this source and can vouch for its reliability and accuracy.

For my purposes I just need an accurate open and close price. If anybody has any experience to share regarding the accuracy of this python module please let me know.

Also if there are any suggestions regarding alternate data sources for historical open and close prices they would be appreciated.

Edit: I am not concerned with accurate adjusted close prices, for the time being just actual close price that occurred the day of.

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  • $\begingroup$ Voted to close as this seems pretty off topic $\endgroup$
    – chollida
    May 12, 2016 at 17:26
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    $\begingroup$ @chollida sorry but how is looking for sources to aggregate accurate market data off topic in a quantitative finance forum? $\endgroup$
    – Mustard Tiger
    May 12, 2016 at 21:30

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Look at matplotlib.finance

It downloads data from yahoo finance as well but it is much quicker than the package that you are mentioning.

Regarding the reliability, I think that the data source is quite reliable.

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  • $\begingroup$ Can you put a number on "quite reliable" or provide a reference? $\endgroup$
    – oliversm
    Jun 13, 2016 at 9:20
  • $\begingroup$ From my experience the closing prices are quite accurate. I don't believe that there is any reference regarding the reliability of Yahoo Finance. I have spotted some inaccuracies in the past such as wrong dividend adjustment but it was quite easy to spot it due to the large jump in stock value. I guess another way to "quantify" the accuracy is the suggestion of michael below $\endgroup$
    – e.mal
    Jun 14, 2016 at 10:10
  • $\begingroup$ That was generally the sort of number I was hoping might be available. i.e. a discrepancy of 1$\sigma$ every 1000 data points, etc. $\endgroup$
    – oliversm
    Jun 14, 2016 at 13:44
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First, if you are using python for this, I would recommend that you take a look at pandas in general and the pandas data reader package

If data reliability is a concern, I recommend that you self-verify by randomly selecting dates and assets, pulling data from multiple sources (like say yahoo, google, and Quandl) and checking them against each other and investigating any discrepancies.

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The biggest problem you face is that prices can be updated over time and I do not think, to the best of my knowledge that Yahoo, will do that for you.

I would recommend a premium data source such as https://www.quandl.com/browse?filterBy=Premium&idx=database-browser_stock-data_united-states_stock-prices-end-of-day-current-and-historical as michael_j_ward stated.

You may also want to give Thomson Reuters Sirca a look as well as Bloomberg BBG ( these resources are great if you know anyone at an academic institution) as well as the Wharton Databases.

Good Luck!

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