[open-economics] Fwd: [okfn-discuss] Open Source Finance Meetup in San Francisco, February 20

Wed Feb 13 20:18:39 UTC 2013

Alexander

Thanks for your response. You are welcome to dial in, although it will be 3:30am CET on 21 February when I start talking!

Several commercial models are available to estimate default probabilities for individual, corporate and structured finance credits. While no model is perfect, these technologies have enjoyed continuous use at banks and other financial institutions for decades. If they didn’t work, I am sure they would fall out of use.

Much of the difference in interest rates across different fixed income asset classes is due to differences in risk estimates by market participants. These investors are informally modeling default risk in their heads.  Since we know from the behavioral economics literature that people aren’t very good at estimating probabilities or weighting multiple factors, surely we can get better results by delegating these tasks to a computer system that incorporates our study of historical patterns and our theoretical understanding of default drivers.

For more on this please see my recent journal article at http://www.econjwatch.org/828.

The issue of “gaming” the model is a serious one.  Once an open source community is established to support a given model, it needs to be able to adapt the model to changes in market conditions. Also, this concern is not unique to open source solutions. In the run up to the financial crisis, issuers adjusted their deal structures to meet published rating agency criteria.

Regards,

Marc

From: open-economics-bounces at lists.okfn.org [mailto:open-economics-bounces at lists.okfn.org] On Behalf Of Alexander Praetorius
Sent: Wednesday, February 13, 2013 11:52 AM
To: Velichka Dimitrova
Cc: open-economics at lists.okfn.org
Subject: Re: [open-economics] Fwd: [okfn-discuss] Open Source Finance Meetup in San Francisco, February 20

I'd like to attend.
I wonder why you think that a calculation could solve the problem.

What leads to the believe, that something as a "default probability" could be calculated at all?

If it is not transparent, then people wonder if they could trust in ratings.
If it is transparent, then people could perfectly anticipate the rating method, rendering the rating obsolete, because Sovereign Debt could be artificially engineered in a way that optimizes the rating, so that the actual rating will never reflect the "true probability of defaulting".

So people will start to interpret the "official open source rating" and the problem will start again :-)

On Wed, Feb 13, 2013 at 8:18 PM, Velichka Dimitrova <velichka.dimitrova at okfn.org> wrote:

---------- Forwarded message ----------
From: Marc Joffe <marc at publicsectorcredit.org>
Date: Wed, Feb 13, 2013 at 4:14 PM
Subject: [okfn-discuss] Open Source Finance Meetup in San Francisco, February 20
To: balug-talk at lists.balug.org, okfn-discuss at lists.okfn.org, bayarea.members at lists.the-hub.net

Last week’s Department of Justice lawsuit against S&P reminds that five years after the financial crisis, the global financial system is still broken and constructive solutions remain out of reach. We believe that open source tools can bring the transparency that this system needs, and have formed a Meetup group in San Francisco to discuss open source /open data finance concepts. 

Our next Meetup is Wednesday, February 20th at 6:00 PM at the offices of Kaggle, 188 King Street Unit 502, San Francisco, CA. To attend in person, please join the Open Source Finance Meetup <http://www.meetup.com/Open-Source-Finance>  group and RSVP. A description of this meeting follows:

Rating agency assessments of sovereign debt have been in the news for some time. In 2011, S&P faced enormous criticism for downgrading the US, while all agencies have been criticized for downgrading Greece too late and for discriminating against emerging market countries. Less is said about US state bond ratings, but interested observers might wonder why California is still rated lower than many toxic assets despite balancing its budget.

Instead of analyst discretion, sovereign and state credit ratings can and should be calculated with transparent, open source computer models. Last year, I introduced such a model - the  <http://www.publicsectorcredit.org/pscf.html> Public Sector Credit Framework - which I will demonstrate. The tool uses a combination of Excel and C to perform a multi-year fiscal simulation on the target government.

No food this time, but we are offering a virtual meeting alternative.  Up to 24 remote attendees can access the session using GoToMeeting. There is no charge for attending a GoToMeeting but you do have to download a small client app. Most major platforms are supported. Details are as follows:

Web Address:  <https://www3.gotomeeting.com/join/463426174> https://www3.gotomeeting.com/join/463426174

Telephone Number: +1 (619) 550-0000 <tel:%2B1%20%28619%29%20550-0000> 

Access Code: 463-426-174

Start Time:  6:30 PM Pacific Standard Time

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Velichka Dimitrova

Open Economics Project Coordinator

Open Knowledge Foundation

http://okfn.org | http://openeconomics.net

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Best Regards / Mit freundlichen Grüßen

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Alexander Praetorius

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[web] http://wiki.piratenpartei.de/Benutzer:Serapath 

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