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As of April 2014, the 32-bit version of kdb+ ist now free (as in beer). KX systems have removed: the 4h timeout the requirement to reinstall every 3 months the restrictive non-commercial license The only limitation vs. the 64-bit version is that you can only address up to 4GB of memory per process. But work around this by writing a multiprocessing system ...


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Github and Bitbucket are both good options for a git repository. If you want other people to look at your code and help build on it, Github is the better choice. If privacy is what matters most, you can get a free private repository from Bitbucket. On github, only public repositories are free.


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Assuming you are at a decent university, you are better off seeing if you can get this data from Bloomberg or from a university subscription to Compustat.


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As background, Floating point precision is a way of storing numbers such that the precision is relative to the largest digit. For instance, the number $0.00123$ stored in fixed precision needs 6 digits of precision (3 zeros and the 3 non-zero numbers). However, this same number stored as floating point precision $1.23 \cdot 10^{-3}$ needs only 3 ...


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Have a look at Kona which is a FOSS project trying to be compatible. Also Tom Szczesny has done some work on its predecessors namely A. I hope this helps. Also if you are not looking for a perfect substitute you can have a look at other Time Series Databases like InfluexDB, Java Chronicles, OpenTSDB, KairosDB which are all Open Source. There are commercial ...


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I don't like KDB+/q. For KDB+ experts, I am not picking a fight. The following is just my own understanding on KDB+ and TimeSeries Database. You're warmly welcome to correct me if anything wrong in your eyes :). First of all, during my near one year's KDB+/q development experience, I never ever find a paper based benchmark result indicating KDB+/q ...


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I've run into this issue as well. I can't find any official documentation, but the issue arises because the SEC makes up CUSIPs for all of the options on the list. It does this by taking the first 6 digits of the underlying equity (which makes sense, as this represents the issuer, which should be the same for the stock and the option), and then for the 7th ...


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kdb+ seems to be the leader but their programming language is a pain really. Personally I use a HDF5. It is a No-SQL database. It integrates very nicely with python. I have been very happy with it so far.


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An alternative is the TeaFiles file format. It's simple and boasts a high performance but I believe you'll have to reinvent some wheels.


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Recently I found a book on earnings trading but did not have time to read thoroughly. Trading on Corporate Earnings News - John Shon I also had spent some time to see earnings surprise effects and it is a quite interesting but not easy to use topic. There is certainly a jump if the estimates and announced earnings have a large mismatch but the magnitude ...


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For any data that is not strictly tabular and unchanging in schema, you should rule out SQL solutions. Option pricing fits that description in my experience, because high-liquidity stocks, currencies, or bonds, will have a far bigger set of strikes and maturities than lower liquidity instruments. Thus in a relational database you will have to have columns ...


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Lots of people focus on data storage ability and compare KDB with other SQL/query-based databases. Such comparison is like considering "Is a Ferrari good for running a bus route?" KDB+ is capable of manipulating and querying large data set. The performance is fast (in comparison to most RDBMS) due to its column based storage, but it's not her strongest ...


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One of the reasons q/kdb+ is attractive for tick data is that it can process data tick by tick as well as using the SQL-like query language. The only system I've used that can process a tick-feed like q/kdb+ is Esper. It is very difficult to work with because it's an embedded language invoked by an Esper runtime environment within a JVM. There are extra ...



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