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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

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.

The Lessons

1. Statistical Entropy

2. Structural Imagination

3. Self-Referential Feedback

4. Complexity and Second Order Uncertainty

5. Alternate Means of Valuation

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

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

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?

Mortgage Default Experience

SOURCE: Mortgage Bankers Association - National Delinquency Survey

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

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

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

2. Structural Imagination

Broad Geographic Distribution

2. Structural Imagination

Through mid-2006

What unobserved contingency could upset this pattern?

Idiosyncratic Causes for Default

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

$ $ $ $

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

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

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

2. Structural Imagination

The Lesson

1) Look for significant unrepresented variables.

2) Track these variables carefully as early warning indicators of emerging problems.

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.

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

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

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

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

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?

5. Alternate Means of Valuation

5. Alternate Means of Valuation

?

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

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)

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

?

A Question

Was this crisis a Black Swan?

?

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)

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.

• 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

Compound Economic

Impact

Recognize that success of an innovation can alter the environment in ways that jeopardize continued success

3. Self-Referential Feedback

Summary

Limited data and untested complexity make risk estimates inherently uncertain

4. Complexity Dark Risk

Summary

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

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