Home > data science, finance, open source tools, rant > Open Source Ratings Model (Part 2)

Open Source Ratings Model (Part 2)

August 12, 2011

I’ve thought more about the concept of an open source ratings model, and I’m getting more and more sure it’s a good idea- maybe an important one too. Please indulge me while I passionately explain.

First, this article does a good job explaining the rot that currently exists at S&P. The system of credit ratings undermines the trust of even the most fervently pro-business entrepreneur out there. The models are knowingly games by both sides, and it’s clearly both corrupt and important. It’s also a bipartisan issue: Republicans and Democrats alike should want transparency when it comes to modeling downgrades- at the very least so they can argue against the results in a factual way. There’s no reason I can see why there shouldn’t be broad support for a rule to force the ratings agencies to make their models publicly available. In other words, this isn’t a political game that would score points for one side or the other.

Second, this article discusses why downgrades, interpreted as “default risk increases” on sovereign debt doesn’t really make sense- and uses as example Japan, which was downgraded in 2002 but still continues to have ridiculously low market-determined interest rates. In other words, ratings on governments, at least the ones that can print their own money (so not Greece), should be taken as a metaphor of their fiscal problems, or perhaps as a measurement of the risk that they will have potentially spiraling inflation when they do print their way out of a mess. An open source quantitative model would not directly try to model the failure of politicians to agree (although there are certainly market data proxies for that kind of indecision), and that’s ok: probably the quantitative model’s grade on sovereign default risk trained on corporate bonds would still give real information, even if it’s not default likelihood information. And, being open-source, it would at least be clear what it’s measuring and how.

I’ve also gotten a couple excellent comments already on my first post about this idea which I’d like to quickly address.

There’s a comment pointing out that it would take real resources to do this and to do it well: that’s for sure, but on the other hand it’s a hot topic right now and people may really want to sponsor it if they think it would be done well and widely adopted.

Another commenter had concerns of the potential for vandals to influence and game the model. But here’s the thing, the point of open source is that, although it’s impossible to avoid letting some people have more influence than others on the model (especially the maintainer), this risk is mitigated in two important ways. First of all it’s at least clear what is going on, which is way more than you can say for S&P, where there was outrageous gaming going on and nobody knew (or more correctly nobody did anything about it). Secondly, and more importantly, it’s always possible for someone to fork the open source model and start their own version if they think it’s become corrupt or too heavily influenced by certain methodologies or modeling choices. As they say, if you don’t like it, fork it.


Update! There’s a great article here about how the SEC is protecting the virtual ratings monopoly of S&P, Moody’s, and Fitch.

  1. August 13, 2011 at 9:49 am

    Release early, release often….


  2. human mathematics
    September 8, 2011 at 1:00 pm

    You’re talking about a model that would predict inflation, then?

    Think about this, then: the Taylor Rule is kind of like an open source model. It’s a widely used touchstone for discussions, based on publicly available data.


  3. April 12, 2012 at 12:07 pm

    I belatedly stumbled across these great posts after publishing my own call for open source credit rating models. See http://expectedloss.blogspot.com/2012/04/credit-rating-agency-models-and-open.html.

    I am releasing an initial version of an open source Public Sector Credit Framework (PSCF). A project like this will only succeed if several smart people collaborate on it. Please contact me if you would like to learn more: marc[at]publicsectorecredit.org.


  1. August 16, 2011 at 6:25 am
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