The new Data Miner stand-alone app (built on top of Portfolio123 API) is now available for use. Data Miner is a Windows application for non-programmers. It can run thousands of unattended operations with ease, speed and reliability. Currently it features several data mining operations, such as rolling screens , rank performance tests, and rank downloads. Data Miner can also be used to download point in time factors (data license required). We’ll be adding several operations soon, so let us know what you think. In addition, we’re also releasing it as an open source project so you can create your own versions or, if you like, contribute to the official release.
This is version 1.0 so bear with us. We think it’s worth releasing it now because it has many nice features that can help you run comparisons between FactSet & Compustat.
You can download Data Miner in the link below. Be sure to download the samples and read the pdf.
The Open Source project will be available soon here:
NOTE: You will need your own private API key. To generate it click on your picture on top right, then Account Settings → Subscriptions → API and click ‘Create’.
Thank you! This has awesome potential (whether I end up being able to use it or not).
I have downloaded it and I have been able to use one of the samples (Ranks-inlined ranking system).
I have a question about labels. None of your samples provide labels: i.e., the returns.
Is that something that can be obtained without a data provider license?
Ultimately to be useful I will need the returns (or labels for supervised learning) and I will have to learn the indexing method to concatenate the returns of a ticker (for a specific week) with the ranks (for that week).
How is this indexed? I do not see what I normally consider an index. Will the P123 UID function as an index?
Ideally, the data would have a hierarchical row index of the date and the ticker for download. The factor ranks would be the column index (along with the label or returns of the next week). Ultimately, I would probably prefer to download the data and run it though Jupiter Notebooks, Colab or Spyder.
I could probably even hire a graduate student to help me with this if need be. So the details of how to do this may not be important in this thread.
Anyway, this is great! And thank you in advance for any information. If I cannot ultimately use this that is probably okay: the price I pay for not taking enough courses in programming. Although, I think you will be rewarded for making this usable for the average graduate with a finance degree (at the undergraduate level). I think you will want to attract people who want to run econometrics models that they learned getting undergraduate finance degrees which may not have involved a lot of programming.
For now my only question is whether a license is required to get data on returns (the label for supervised learning). If a license is requried, I will probably continue using what P123 already offers without spending a lot of time on learning how to use this addition now.
In the “RanksPeriod” example a member can substitute the name of a ranking system that they have already created as well as a universe they have already created.
This can be done over an extended period as the name implies (with dates in the column).
That is a lot of information that can be downloaded all at once.
It looks like this has a lot of potential. Some data wrangling will be required with version 1.0 but a lot of information can be downloaded already and there seems to be a lot of potential for the future version.
To specify this, you’ll need to put the expression in quotes: [font=courier new]“#AnalystsCurQ”[/font]
If the expression also has double quotes in it, you’ll need to prefix those quotes with a backslash for it to work: [font=courier new]“FRank("#AnalystsCurQ")”[/font]
I can’t get your second tip to work, take this example it gets this error:
2020-05-12 22:50:41,089: API request failed: Element type “StockFormula” must be followed by either attribute specifications, “>” or “/>”. (on line 2)
YAML uses a few special characters, documentation on how to deal with them when present in property values (eg formulas) can be found in the README.txt on dropbox.
A new release that addresses a bug exposed by Quantonomics’ example has also been uploaded.