Category Archives: mathematica

New release of the Bloomberg-to-Mathematica link

Those who use Bloomberg and Mathematica should find this useful. This interface allows the direct loading of Bloomberg data (historical prices, bulk data like dividends, current data like stock prices, etc.) into Mathematica. I’ve made the interface freely available since 2008, but this release represents the largest changes in over six years. Most importantly, it can now handle bulk data like current holders of a security and historical dividends, and it’s much more robust about errors.

Historically I’ve thrown source code in the .zip file with the binaries but starting with this release, the source code and the binaries will be in separate GitHub repositories. See https://github.com/MichaelSternNYC for everything. If you just want to install the links, check out https://github.com/MichaelSternNYC/bloomberg-to-mathematica in particular.


histLink = msBBGgetHistoryMakeLinkObject[];

x1 = msBBGgetHistory["IBM US Equity", "Px_Last", {2014, 1, 1}, "",
"Day", "use DPDF" -> False, LinkObject -> histLink];
x2 = msBBGgetHistory["IBM US Equity", "Px_Last", {2014, 1, 1}, "",
"Day", "use DPDF" -> True, LinkObject -> histLink];
DateListPlot[{x1, x2}, PlotStyle -> {Orange, Purple},
PlotLabel -> "IBM Stock Price via the new interface",
ImageSize -> Large,
Epilog -> {(Text[
Style["not dividend-adjusted", FontFamily -> "Times New Roman",
FontSize -> 10, Orange], {{2015, 1, 22}, 169}]),
(Text[Style["dividend-adjusted", FontFamily -> "Times New Roman",
FontSize -> 10, Purple], {{2015, 1, 22}, 140}])
}]

demo of the new interface

Significant update to the Bloomberg to Mathematica link

I’ve been making significant changes to the Bloomberg-to-Mathematica link recently, including

  1. the ability to specify whether historical data has DPDF adjustments (in other words, whether or not prices have been adjusted for dividends, splits, and other capital events),
  2. the ability to pull bulk data like historical dividend records and current holders, and
  3. the ability to keep the link live between queries, significantly reducing latency.

Other improvements include more sophisticated handling and reporting of errors and more widespread use of modern Mathematica data types (Associations and TimeSeries). I will provide all the source code, perhaps in the form of a GitHub depository. The new and improved functions are based on Wolfram’s current WSTP libraries and the current version of the Bloomberg BLP API. I’ve built to 32-bit architecture but I believe that 64-bit versions should be possible as well.

I’m waiting for Bloomberg to help with one source of crashes (when a company announces a distribution but cancels it before record date). When that’s taken care of I will upload the improved binaries and interfaces, etc. Those who want to play with the source code should visit https://github.com/MichaelSternNYC

[update March 7, 2016: the new executables are also available on Github, at https://github.com/MichaelSternNYC/bloomberg-to-mathematica]

New Bloomberg-to-Mathematica interface for Mathematica 10

I have added a new interface notebook for those using Mathematica 10. It fixes some bugs, increases flexibility, and most importantly, takes input and produces output using Mathematica’s new date and temporal data types, and using an Association rather than a list. It’s cleaner and more robust than the old method (though the old notebook will continue to work for those afraid of change.) If you upgrade from the old interface to the new one, note that all the functions have changed names, and their default installation path has changed as well. It’s all documented in the new notebook in the zip file at

http://www.wheels.org/monkeywrench/wp-content/uploads/2013/02/bloomberg_to_mathematica.zip

Sample usage of the new version:

aaplNF2 = msBBGetNF2["AAPL Equity", "Px_Last", DateObject["20070901"], DateObject["20081020"], "day"]; ibmNF2 = msBBGetNF2["IBM US Equity", "Px_Last", DateObject["20070901"], DateObject["20081020"], "day"];
DateListPlot[{aaplNF2[["data"]], ibmNF2[["data"]]}, Frame -> {True, True, False, False},
PlotLabel -> "IBM and Apple in 2007 and 2008", Epilog -> {(Text["apple", {{2008, 8, 1}, 18}]), (Text["ibm", {{2008, 8, 1}, 110}])}]

ex50

[ March 4, 2016 Update coming. See http://www.wheels.org/monkeywrench/?p=834 ]
[ March 7, 2016: the new source code and executables are available on Github, at https://github.com/MichaelSternNYC The Win32 binaries and instructions for use can be found at https://github.com/MichaelSternNYC/bloomberg-to-mathematica]

Mathematica 10

Things I particularly like about Mathematica 10.

1. Multiple undo

It undoes both the typing and the results of one’s typing. Yay.

2. Curated APIs

Mathematica can now natively communicate with a number of online services, tweeting or analyzing one’s tweets, downloading images from instagram, making association graphs of one’s facebook friends, and so forth.

I have in the back of my mind to set up an IP camera that Mathematica monitors, and that tweets when it detects specified activities. It would take only about three lines of code.

In practice, so far, I’ve been using it mostly with RunKeeper.

runkeeper = ServiceConnect["RunKeeper", "New"];
ServiceExecute[runkeeper, "UserData"];
id = First[runkeeper["FitnessActivities"]]["ActivityID"];

runkeeper["AnimatedPathMap", {"ActivityID" -> id,
AnimationRunning -> False}]

map

The major weaknesses here are (a) not every service that Wolfram connects to publishes the information that you want via their API. So, for example, while there is the great FriendNetwork from Facebook and FollowsNetwork from Twitter, there is nothing comparable from LinkedIn. Further, sometimes the service does make information available but Mathematica gives you no way to query it. For example, the RunKeeper connection would be about a million times more useful to me if I could pull HRM data as well as the geopath. RunKeeper can provide it, but Mathematica 10 doesn’t know how to ask. Perhaps if enough of us complain about its abence, Wolfram will respond.

3. Associations

One could create structured lists before, but this is vastly more flexible. Instead of

{name, age, street address}

where the form is rigid and can be confusing especially for long records with mostly blank entries, and where the form must be carefully documented for there will be any hope of reusing the data or the code that interpreted it, one can now do

In[59]:= item1 = <|name -> "bill smith", age -> 37, streetAddress -> "121 Main Street"|>;

In[60]:= Lookup[item1, name]

Out[60]= "bill smith"

In[66]:= addressbook = {<|name -> "bill smith", age -> 37,
streetAddress -> "121 Main Street"|>, <|name -> "susan smith",
streetAddress -> "121 Main Street"|>};

In[67]:= Map[Lookup[#, name] &, addressbook]

Out[67]= {"bill smith", "susan smith"}

One can also combine elements from multiple associations into a single record, something that would have been more difficult with the old method.

4. Wolfram Cloud deployment

This is not as good for Manipulate[] as the Mathematica plugin, but far more accessible.

In[8]:= CloudDeploy[
runkeeper["AnimatedPathMap", {"ActivityID" -> id, AnimationRunning -> True}],
Permissions -> "Public"]

Out[8]= CloudObject["https://www.wolframcloud.com/objects/221ebde8-c287-46db-b602-\
e0f5cde8a5e7"]

Other thoughts

Templating and, in particular, automated report generation, would have been useful in my last job. I’m not sure about this one but it feels as though it may come in handy.

Wolfram has improved support for the standardized time series datatype that they introduced in, I think, version 9. I’ve been using a homegrown method since long ago and the Wolfram version is lacking a lot of functionality still (the ability to do math between time series, dividing one by another, for example. The ability to normalize a time series, etc.). Together with the ability to manipulate metainformation (introduced in version 9), this is now a clean way of handling financial information. I expect to start migrating my code over to use the new format.

IRR and NPV in Mathematica, the modern way

Back in 2010 I posted an explanation of how to compute net present values and internal rates of return in Mathematica. It worked but it was a little verbose. Considering that Mathematica can do things like optical character recognition with a single command, it seemed a shame that it couldn’t do these basic financial functions.

Wolfram has fixed this, and computing IRR and NPV in Mathematica is now much more civilized.

Using the same sample cash-flow as last time (but reformatting the date to list-format, as Mathematica’s Cashflow[] function demands for some reason),

testFlow = {{{2001, 1, 1}, -1}, {{2002, 1, 1}, .3}, {{2005, 1, 1}, .4}, {{2005, 1, 10}, .5}};

TimeValue[Cashflow[testFlow], .05, {2001, 1, 1}]

returns an NPV of .0256519, just as it should. And

FindRoot[TimeValue[Cashflow[testFlow], r, {2001, 1, 1}] == 0, {r, .05}]

gives us the IRR, in this case .0584316.

Mathematica clearly performs a compilation the first time my NPV is run, and while the native NPV and IRR computations are quicker than mine the first time one of them is run by about a factor of 50, the second time one of them is run (whether on the same data or not) my code is quicker than theirs by about 30%. Mine is also ecumenical about date formats, but in practice I find myself using their code anyway, as it is so concise.