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Etech2009

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Jesper Andersen and Toby Segaran's ETech talk introducing Freerisk.

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Etech2009

  1. 1. I Just Don’t Trust You: Can Engineers Change Credit Etech Presentation 3/10/09
  2. 2. LEHMAN BROTHERS – 9/14/2008 MOODY’S:A2
  3. 3. LEHMAN BROTHERS – 9/15/2008 MOODY’S: CCC
  4. 4. ENRON 11/27/2001 Moody’s: Baa3
  5. 5. Enron 12/04/2001 • Moody’s: Ca 5
  6. 6. AIG Moody’s: AAA
  7. 7. AIG 9/15/2008 Moody’s:A3 Treasury Text negotiates Text terms with Moody’s for follow-on investments
  8. 8. There are two superpowers in the world today in my opinion. There's the United States and there's Moody's Bond Rating Service... And believe me, it's not clear sometimes who's more powerful. Friedman, 1996 Thomas 8
  9. 9. CREDIT AGENCIES ARE BROKEN SAFETY NETS
  10. 10. Nationally Recognized Statistical Rating Organization Moody’s Standard and Poor’s Fitch PROTECTION Securitized Bonds Mutual Funds Government Bonds Government Investing Corporate Bonds Retirement Accounts Structured Debt Pension Funds
  11. 11. Credit Risk Measures
  12. 12. Structura l Problems Beget Moral Failures
  13. 13. Who would you pay to rate your Moody’s S&P Fitch
  14. 14. This kind of bribery doesn’t send
  15. 15. Payments Create Bad Ratings
  16. 16. They Has
  17. 17. NRSRA Enjoy Patent Like Without Patent Like
  18. 18. What makes “AAA” more meaningful than a gold
  19. 19. Today's rating action follows the collapse in market confidence in the firm, and Lehman's announcement that it was filing for Chapter 11 bankruptcy protection after its failure to reach a merger agreement with a stronger strategic partner. Moody’s Press Release - 9.15.2008
  20. 20. Opacity Create Bad Ratings
  21. 21. “The CDO World Relied Almost Exclusively on this Copula Based Correlation Model” Darrel Dufiem – Moody’s Janet Tavakoli – Tavoki Structured “Correlation Trading Has Spread Through The Psyche of the Financial Markets Like a Highly Infectious Through Virus”
  22. 22. Consensus Doesn’t Explore Options
  23. 23. Model Risk: Are We Doing This
  24. 24. Contrarian Investing Is Forbidden Fruit Most mutual funds, pension funds must invest in highly rated bonds
  25. 25. If you permit forbidden fruit, everyone will want then
  26. 26. Lack Of Ecosystems Create Bad Ratings
  27. 27. Risks Are Hidden
  28. 28. Some Risks Are Unknowable
  29. 29. Good Predictions Are Ignored
  30. 30. Celebrated After The Fact
  31. 31. Or Only Have Incentives For Secrecy
  32. 32. Single Sourced Information Creates Bad Ratings
  33. 33. 33
  34. 34. $45,000,000,000,
  35. 35. A Lot of A Lot of Big Dangerous Problems Problems
  36. 36. Engineers Have Requirements, Not Problems
  37. 37. FRS: Rating Creation Needs To Be FRS: Rating Needs To Be Open FRS: Ratings Need To Be Diverse FRS: Ratings Needs Transparency
  38. 38. Commons
  39. 39. NOT DIGG
  40. 40. Not “discussion” boards
  41. 41. Freerisk is an... Authoritative Data Source User Contributed Data Source Set of Contributed Algorithms Testing Framework
  42. 42. Open Data
  43. 43. XBRL Is Hard Standard of Standards 13 Legal Jurisdictions + 4 Provisional 3500 Defined Elements 100s of use cases 43 Taxonomies
  44. 44. Quarterly Statement 2008-03 $14.5 period statemen revenue Quarterly $41.5 current Microsoft Statement statemen freerisk:tob $27 billon current by liabilities statemen footnote User annotatio Annual Footnote-2 assertions Statement ??? ??? ??? ???
  45. 45. JSON { quot;2007quot;: { quot;http://xbrl.us/us-gaap/2008-03-31#OtherAssetsCurrentquot;: quot;9162000quot;, quot;http://xbrl.us/us-gaap/2008-03-31#Revenuesquot;: quot;19332000quot;, quot;http://xbrl.us/us-gaap/ 2008-03-31#AccountsReceivableNetCurrentquot;: quot;1901000quot;, quot;http://xbrl.us/us-gaap/2008-03-31#TreasuryStockValuequot;: quot;23070000quot;, quot;http://xbrl.us/us-gaap/2008-03-31#ShortTermInvestmentsquot;: quot;11196000quot;, quot;http://xbrl.us/us-gaap/2008-03-31#StockholdersEquityquot;: quot;336377000quot;, quot;http://xbrl.us/us-gaap/ 2008-03-31#SellingAndMarketingExpensequot;: quot;26571000quot;, quot;http://xbrl.us/us-gaap/2008-03-31#AccountsPayablequot;: quot;30058000quot;, quot;http://xbrl.us/us-gaap/2008-03-31#Liabilitiesquot;: quot;97207000quot;, quot;http://openrisk.org/terms/periodquot;: quot;2007quot;, quot;http://xbrl.us/us-gaap/2008-03-31#AssetsCurrentquot;:
  46. 46. Open API
  47. 47. You Too, Can Make a Risk Calculator Implement 2 Restful Calls /query? company=fb:en.microsoftperiod=200 7 /defaultRisk?data={jsonstring}
  48. 48. Free To See Anyone’s Results http://freerisk.org/api/getcreditscore? source=http://mycalculator.com/ baseurl company=fb.en.microsoft.com period=2008 http://freerisk.org/api/ rankbycreditscore?source=http://
  49. 49. class CreditController ApplicationController def query render :text = sqarquery end def defaultRisk hash_data = JSON::parse(params[:data]) render :text calculate(hash_date).to_json end
  50. 50. class Score: @cherrypy.expose def query(self, company, period): return sparquery @cherrypy.expose def defaultRisk(self, data): rec=loads(data) return dumps({'score' : calc(rec}) 54
  51. 51. Automatically Test Your Score IF YOU GET Your score is monotonic Covariance with defaults Your score goes up for better
  52. 52. Compare Your Scores With
  53. 53. Piotroski Score 1.Positive Net Income (+1 for each) 2.Positive Cash Flow 3.Return on Assets up 4.Cash Flow Net Income 5.Debt / Assets up 6.Current Ratio increased 7.#Shares Outstanding same 8.Gross Margin last year 9.% increase Sales the % increase Total Assets.
  54. 54. Altman Z-Score Z-Score = EBIT/Total Assets x 3.3 + Net Sales /Total Assets x 0.99 + Market Value of Equity / Total Liabilities x 0.6 + Working Capital/Total Assets x 1.2 + Retained Earnings /Total Assets x 1.4 58
  55. 55. LEH 3 2 Value Title 2 1 0 -1 May 31, 07 August 31, 07 Feb 29, 08 May 31, 08 Category Title
  56. 56. AIG 3 2 Value Title 2 1 0 -1 Dec, 07 Apr, 08 Jun, 08 Sep, 08 Category Title
  57. 57. MSFT 7 5 Value Title 4 2 Apr, 08 Jun, 08 Sep 29, 08 Dec 31, 08 Category Title
  58. 58. Whe re D Her oW e? eG o Fr om
  59. 59. We think you wouldld like to help us.
  60. 60. Data Completeness Complete XBRL for US Based Schemas Support for non-XBLR US data sources Complete XBRL for non-US Based Schemas Support for non-XBLR non-US data
  61. 61. There’s every reason to believe that with your help we can beat the NRSRO’s
  62. 62. Catch-22: Becoming a Nationally Recognized Statistical Rating Organization Requires National Recognition 66
  63. 63. “...we have to turn the risk management problem on its head if we are to make any progress in opening the models that today are holding back insight into collective risks.”
  64. 64. Thanks

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