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www.sungard.com
Lessons for Financial Risk Management from the Great Recession
David M. Rowe, Ph.D.
EVP for Risk Management – SunGard Adaptiv
Nykerdit Symposium 2009
Copenhagen, Denmark
October 26, 2009
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Sage Advice
Learn from the mistakes of others,
you'll never live long enough to make them all yourself.
It’s also less painful than learning from your own mistakes.
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The Lessons
1. Statistical Entropy
2. Structural Imagination
3. Self-Referential Feedback
4. Complexity and Second Order Uncertainty
5. Alternate Means of Valuation
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1. Statistical Entropy
Statistical analysis can extract information from data, it cannot create information not already contained in the data.
Stated more casually:
Like water, information cannot rise higher than its source.
Data
Information
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Info
r m ai
ton
Information
Data
o Info
r m ai
t
n
This is extraction of information,
NOT creation of information
1. Statistical Entropy
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Extreme Confidence Estimates
AAA
AA
A
BBB
BB
B
CCC
1 annual default every 10,000 years!
Alternately
AAA AAA AAA AAA AAA AAA AAA AAA AAA AAA
AAA AAA AAA AAA AAA AAA AAA AAA AAA AAA
AAA AAA AAA AAA AAA AAA AAA AAA AAA AAA
AAA AAA AAA AAA AAA AAA AAA AAA AAA AAA
AAA AAA AAA AAA AAA AAA AAA AAA AAA AAA
AAA AAA AAA AAA AAA AAA AAA AAA AAA AAA
AAA AAA AAA AAA AAA AAA AAA AAA AAA AAA
AAA AAA AAA AAA AAA AAA AAA AAA AAA AAA
AAA AAA AAA AAA AAA AAA AAA AAA AAA AAA
AAA AAA AAA AAA AAA AAA AAA AAA AAA AAA
1 annual default every century
Super-senior tranches of subprime mortgage-backed securities were rated AAA (or BETTER!!)What was the empirical basis for these ratings?
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Mortgage Default Experience
SOURCE: Mortgage Bankers Association - National Delinquency Survey
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Hypothetical Detachment Point
Hypothetical Subprime Default Probability Density
-
0.0500
0.1000
0.1500
0.2000
0.2500
0 5 10 15 20 25
Defaults (%)
Pro
bab
ilit
y D
ensi
ty
Log-Normal Distribution: Mean = 5.97; StDev = 2.16
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Hypothetical Detachment Point
Hypothetical Subprime Default Probability Density
-
0.0500
0.1000
0.1500
0.2000
0.2500
0 5 10 15 20 25
Defaults (%)
Pro
bab
ilit
y D
ensi
ty
.01% = AAA
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Hypothetical Detachment Point
Hypothetical Subprime Default Probability Density
-
0.0500
0.1000
0.1500
0.2000
0.2500
0 5 10 15 20 25
Defaults (%)
Pro
bab
ilit
y D
ensi
ty
.01% = AAA
Largest Sample Observation = 9.6%
Behavior in the Tail is Based on What Distribution is Assumed
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2. Structural Imagination
Broad Geographic Distribution
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2. Structural Imagination
Through mid-2006
What unobserved contingency could upset this pattern?
Idiosyncratic Causes for Default
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2. Structural Imagination
Threats to Diversification
One candidate was fairly obvious.
Falling housing prices would hurt ALL borrowers
Defaults would no longer be statistically independent
$ $ $ $
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2. Structural Imagination
12-month % change
10 City Composite U.S. Home Price Index
12
-mo
nth
% c
ha
ng
e
S&P/Case-Shiller Home Price Indices
Strongly Positive: 1995-2006
Jan
-95
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2. Structural Imagination
10 City Composite U.S. Home Price Index
Aug 1990
Mar 1994
12
-mo
nth
% c
ha
ng
e
S&P/Case-Shiller Home Price Indices
12-month % change
Negative for 3-1/2 years in early 1990s
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2. Structural Imagination
10 City Composite U.S. Home Price Index
12
-mo
nth
% c
ha
ng
eM
on
thly
% C
ha
ng
e (
an
nu
al
rate
)
September 2005
Month-to-Month % ChangePeaked in September 2005 : Turned Negative in mid-2006
Aug 1990
Mar 1994
S&P/Case-Shiller Home Price Indices
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2. Structural Imagination
The Lesson
1) Look for significant unrepresented variables.
2) Track these variables carefully as early warning indicators of emerging problems.
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3. Self-Referential Feedback
The Seeds of Self-Destruction
The huge expansion of subprime mortgage debt set the stage for a more serious crisis when conditions began to worsen.
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An Explosion in Subprime Mortgage Originations
Subprime Mortgage Originations
0
100
200
300
400
500
600
700
2001 2002 2003 2004 2005 2006 2007
700
600
500
400
300
200
100
0
100
25%
20%
15%
10%
5%
0%2001 2002 2003 2004 2005 2006 2007
$ Billions Per year Percent
$150-$200 billion and 6% to 7% of originations
Over $600 billion and Over 20% of originations
By one estimate in late 2007, 14% of all outstanding mortgages were subprime
Source: Inside Mortgage Finance
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3. Beware Self-Referential Feedback - 1
Achieving Greater Volume Required
Relaxing Underwriting Standards
Risk Estimates Based on
Historical Data Become
Progressively Less Reliable
Further
Innovations (e.g. Compound
Repackaging, CDO2 ) Increased
Complexity
DARKRISK
A Unique Innovation Generated Attractive
Returns
Growth in Volume
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3. Beware Self-Referential Feedback - 2
Defaults are Magnified by the Inflated Volume of
Poorly Collateralized
Mortgages
More Stringent Credit
Conditions and Increased
Liquidation Sales
Credit Losses Hurt Bank Earnings
Compound Economic
Impact
An Initial Economic Shock
Home Price Declines
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4. Complexity and Dark Risk
+
Complexity
0
0.05
0.1
0.15
0.2
0.25
0.3
0 5 10 15
Defaults (%)
Pro
bab
ilit
y D
ensi
ty
Limited Data
Dark Risk
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5. Alternate Means of Valuation
Old Credit Risk Mantra What is the second means of repayment?
Proposed Capital Markets MantraWhat is the second means of valuation?
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5. Alternate Means of Valuation
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5. Alternate Means of Valuation
?
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5. Alternate Means of Valuation
Subprime CDOs (2006)
Corporate CDOs (2006)
CDS
IRS
Ease of Current Valuation
Level 1 Observable prices in active markets
Observable prices in inactive markets or observable inputs to accepted pricing models
Few or no observable market prices and models requiring significant unobservable inputs
Level 2
Level 3
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5. Alternate Means of Valuation
Level 1
Level 2
Level 3
Ease of Current
Valuation
Effectiveness of Alternate Means of Valuation Level 2 Level 3
IRS
CDS (2006)
Corporate CDOs (2006)
Subprime CDOs (2006)
Level ?
Level ?
Corporate CDOs (2008)
Subprime CDOs (2008)
CDS (2008)
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Estimated US Banks Balance Sheet (2008 Q2)
$11,950 Bill
L i a b i l i t i e s
Equity $1,351 Bill
Subprime Related
A l l O
t h e r A s s e t s
$540 Bill
$12,761 Bill
Subprime Related Assets
Equity
?
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A Question
Was this crisis a Black Swan?
?
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Product Complexity
Pace of Innovation
Volume GrowthCommodity
Prices
Geopolitical Risk
Information Security
Extreme Events
Model RiskLiquidity
Technological Change
Emerging Markets Operational Risk
Regulatory Uncertainty
Effective Portfolio Mgt.
External Linkages
???? Unknown Unknowns ????Miscellaneous
Elements of the Risk Puzzle (Original: May 2006)
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Product Complexity
Pace of Innovation
Volume GrowthCommodity
Prices
Geopolitical Risk
Information Security
Extreme Events
Model RiskLiquidity
Technological Change
Emerging Markets Operational Risk
Regulatory Uncertainty
Effective Portfolio Mgt.
External Linkages
???? Unknown Unknowns ????Miscellaneous
Elements of the Risk Puzzle (Rev: October 2008)
Pace of Innovation
Product Complexity
Model Risk
Volume Growth
External Linkages
Liquidity
Commodity Prices
Effective Portfolio Mgt.
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• Use structural imagination to define significant unrepresented variables in existing risk analysis
• Track these variables as early warning indicators
2. Structural Imagination
Summary
1. Statistical Entropy
Data
Information
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Compound Economic
Impact
Recognize that success of an innovation can alter the environment in ways that jeopardize continued success
3. Self-Referential Feedback
Summary
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Limited data and untested complexity make risk estimates inherently uncertain
4. Complexity Dark Risk
Summary
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Limit holdings of assets with no reasonably objective second means of valuation even if they are highly liquid today
5. Second Means of Valuation
?
Summary
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A Final Thought – Strategic Risk
“Give me 15% more than last year. Don’t give me excuses, give me the numbers.”
≠ sound aggressive management
= recipe for disaster
Where the buck stops CEO
Board of Directors