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Your best bet might be to find lists of the companies on each exchange and cross-reference them with a list of the companies on the Russell 2000. It shouldn't be too hard to write a little script in python or something that does the comparison for you. It appears that nasdaq.com has a tool that allows you to download csv lists of the stocks listed on the ...


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First consider if you really need to be connected to just the Nasdaq or should you be using a broker that can connect you to all exchanges. Almost certainly the answer is the later. If that is the case then Interactive Brokers is probably the way you want to go. I've setup several CTAs to get started with IB and its probably the best 3rd party to get ...


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First, have a look at Market Microstructure in Practice (Laruelle et L) to have generic explanations about all this. In short: Equity markets are fragmented: it means to buy or sell shares, you connect (via a broker) to a server on which you send a message with a side (buy or sell), a max/min price and a quantity. these servers are technically matching ...


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As suggested by @Bob Jansen: QA Direct - it is quite expensive though. I've used it in past in the form MS SQL database. It has good enough documentation and query like the one in the question are quite possible to implement in single SQL statement.


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The built in data does not seem go quite 5 years back, but you can access dividend data within Mathematica / WolframCloud as well: FinancialData["NASDAQ:AAPL", "Dividend", {"Jan. 1, 2010,", "Nov. 4, 2015"}] To get a list of all symbols on the NASDAQ: list = FinancialData["NASDAQ:*", "Lookup"] To get/organize data for several symbols on this list (first ...



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