New answers tagged market-data
I am and have been a silver member for 3 years with EODDATA. I have had no problems. BTW I write my own code and have a degree in Economics and am a former computer systems analyst. I download their data about once a week. I do not care about hourly price fluctuations or Milan stock exchange or commodities. I am just a simple and profitable investor in the ...
If I understand your question correctly, you're asking what's a good design for a normalized feed. This is a somewhat trivial question of (i) picking which data fields (e.g. price, volume) to filter out from each feed and (ii) how to keep that in a trading system with minimal computational overhead. Regarding (i) I highly recommend you approach this in a ...
Yes, those are probably the variables that predict the better the stock market return. However, the OOS evidence is usually weak. Goyal & Welch provide a good summary on predictors: http://rfs.oxfordjournals.org/content/21/4/1455.abstract
Simply put, no, you won't find this. The most basic one-port ITCH feed with no redistribution rights runs \$750/mo. Historical ITCH data which is useful for backtesting is \$1,000/mo. with a 12 month initial minimum contract. Fees for distributors are much, much more expensive (all costs can be found on the NASDAQ OMX website), and the restrictions on ...
If you are using Bloomberg then you can pull prices adjusted for corporate actions such as splits, dividends, and other capital adjustments, assuming this meets your needs (i.e. momentum based quant strategies). If you know which global equity indices to track then you can pull the historical constituents to minimise survivorship bias. In Bloomberg, MSCI ...
In my humble opinion, the most volatile day during the week should be monday, since it is the day that incorporates the greater number of information that are still not incorporated by the price, but I never tested by myself, so, as you suggested monday-to-monday returns should be different from tuesday-to-tuesday. The literature suggests different solution ...
You can find a good overview here: Seasonal Anomalies by Ziemba, W.; Dzahabarov, C. Abstract: This chapter is a survey of seasonal anomalies. Ziemba has been involved in the re- search and trading of such anomalies as the January turn-of-the-year effect since 1982. His research plus that of other academics plus the very useful practitioner ...
Check out Barchart Ondemand, they just released a Free market data api and they offer real-time and delayed market data apis... I would test out their api http://freemarketdataapi.barchartondemand.com before. I'm currently using it and its very easy to use.
Quote: Starting in 2003, the NYSE started disseminating automatically, with a software called autoquote, any change in the best quotes in its listed stocks. Before that specialists had to update manually new inside quotes in the LOB. This implementation considerably accelerated the speed at which algorithmic traders receive information Endquote Source: ...
The Federal Reserve bank of St Louis has a widely used and popular application called FRED http://research.stlouisfed.org/fred2/ which is a fairly rich data source for US macro time series data considering that it's freely available! Check out their API https://api.stlouisfed.org for more info.
Every exchange in North America sells their historical data. NYSE and Nasdaq are the one's I'm most familiar with. They will sell you the data on a one off instance, ie no monthly fees, just a single flat rate.
Historical intraday data for S&P500 going back to the 1980's is available from Tickdata.com . It is not free.
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