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I have a decade of experience as a software engineer, but little quantitative finance knowledge. I have an idea for a simple trading strategy based around moving averages. In order to test it, I'd like to benchmark the algorithm against historical data sets for some publicly traded US tickers.

My question is mostly around the mechanical act of actually doing this.

Where can I obtain these data sets? Either in downloaded files, or via web API?

Ideally, these would be free. I don't need high resolution or any special features. Basically just a daily quote for some major US companies, tabulated nicely into a CSV or some other structured data. Actually, a simple flat file download would be preferable, as I don't want to be hammering some API and incurring latency, limits, and/or potential cost.

Thanks!

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Recently I came across interesting platform. https://www.quantopian.com/

they offer exactly what you need and for free. Basically, you code your algo in python, they provide data using api and backtesting.
Hope it helps.

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    $\begingroup$ Add quantconnect to the answer as well - they even offer tick data which quantopian doesnt. $\endgroup$ – novice Sep 6 '16 at 2:50
  • $\begingroup$ as I understand it, quantopian only provides data for the stocks and they working on futures $\endgroup$ – chester89 Oct 18 '16 at 9:27
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If you are by any chance familiar with R take a look at the following post LINK

It offers an easy way to obtain data from Yahoo finance, Google etc.

Cheers.

PS: Jameson, I am in a similar situation as you are. I was digging a bit deeper a found also Quandl

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I have used https://www.tickdata.com/ and https://www.quantgo.com/ I enjoy the simplistic nature of obtaining data that they use, so for someone new to quantitative finance like you, I recommend that you try them. https://www.quandl.com also have excellent quality data, easy to use APIs

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