lessons for financial risk management from the great recession
Download
Skip this Video
Download Presentation
Lessons for Financial Risk Management from the Great Recession

Loading in 2 Seconds...

play fullscreen
1 / 36

Lessons for Financial Risk Management from the Great Recession - PowerPoint PPT Presentation


  • 76 Views
  • Uploaded on

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,

loader
I am the owner, or an agent authorized to act on behalf of the owner, of the copyrighted work described.
capcha
Download Presentation

PowerPoint Slideshow about ' Lessons for Financial Risk Management from the Great Recession' - maegan


An Image/Link below is provided (as is) to download presentation

Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author.While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server.


- - - - - - - - - - - - - - - - - - - - - - - - - - E N D - - - - - - - - - - - - - - - - - - - - - - - - - -
Presentation Transcript
lessons for financial risk management from the great recession

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
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
The Lessons
  • Statistical Entropy
  • Structural Imagination
  • Self-Referential Feedback
  • Complexity and Second Order Uncertainty
  • Alternate Means of Valuation
1 statistical entropy
1. Statistical Entropy

Data

Information

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.

1 statistical entropy1
1. Statistical Entropy

I

o

n

r

o

f

i

a

t

n

m

This is extraction of information, NOTcreation of information

Data

I

o

n

r

o

f

i

a

t

n

m

Information

extreme confidence estimates
Extreme Confidence Estimates

Alternately

1 annual default every century

 1 annual default every 10,000 years!

AAA

AA

A

BBB

BB

B

CCC

Super-senior tranches of subprime mortgage-backed securities were rated AAA (or BETTER!!)

What was the empirical basis for these ratings?

mortgage default experience
Mortgage Default Experience

SOURCE: Mortgage Bankers Association - National Delinquency Survey

hypothetical detachment point
Hypothetical Detachment Point

Hypothetical Subprime Default Probability Density

0.2500

0.2000

0.1500

Probability Density

0.1000

0.0500

-

0

5

10

15

20

25

Defaults (%)

Log-Normal Distribution: Mean = 5.97; StDev = 2.16

hypothetical detachment point1
Hypothetical Detachment Point

Hypothetical Subprime Default Probability Density

0.2500

0.2000

0.1500

Probability Density

0.1000

0.0500

-

0

5

10

15

20

25

Defaults (%)

.01% = AAA

hypothetical detachment point2
Hypothetical Detachment Point

Hypothetical Subprime Default Probability Density

0.2500

0.2000

0.1500

Probability Density

0.1000

0.0500

-

0

5

10

15

20

25

Defaults (%)

Largest Sample Observation = 9.6%

Behavior in the Tail is Based on What Distribution is Assumed

.01% = AAA

2 structural imagination
2. Structural Imagination

Broad Geographic Distribution

2 structural imagination1
2. Structural Imagination

Through mid-2006

Idiosyncratic Causes for Default

What unobserved contingency could upset this pattern?

2 structural imagination2
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 imagination3
2. Structural Imagination

12-month % change

Strongly Positive: 1995-2006

10 City Composite U.S. Home Price Index

12-month % change

Jan-95

S&P/Case-Shiller Home Price Indices

2 structural imagination4
2. Structural Imagination

Mar 1994

Aug 1990

12-month % change

Negative for 3-1/2 years in early 1990s

10 City Composite U.S. Home Price Index

12-month % change

S&P/Case-Shiller Home Price Indices

2 structural imagination5
2. Structural Imagination

September 2005

Mar 1994

Aug 1990

Month-to-Month % Change

Peaked in September 2005 : Turned Negative in mid-2006

10 City Composite U.S. Home Price Index

12-month % change

Monthly % Change (annual rate)

S&P/Case-Shiller Home Price Indices

2 structural imagination6
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
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
An Explosion in Subprime Mortgage Originations

700

25%

Over $600 billion and

Over 20% of originations

600

20%

500

15%

400

300

10%

200

5%

$150-$200 billion and

6% to 7% of originations

100

100

0

0%

2001

2002

2003

2004

2005

2006

2007

Subprime Mortgage Originations

$ Billions Per year

Percent

Source: Inside Mortgage Finance

By one estimate in late 2007, 14% of all outstanding mortgages were subprime

3 beware self referential feedback 1
3. Beware Self-Referential Feedback - 1

Risk Estimates Based on Historical Data Become Progressively Less Reliable

Growth in Volume

DARK

RISK

Achieving Greater Volume Required Relaxing Underwriting Standards

Further Innovations (e.g. Compound Repackaging, CDO2 ) Increased Complexity

A Unique Innovation Generated Attractive Returns

3 beware self referential feedback 2
3. Beware Self-Referential Feedback - 2

More Stringent Credit Conditions and Increased Liquidation Sales

Home Price Declines

CompoundEconomic Impact

Defaults are Magnified by the Inflated Volume of Poorly Collateralized Mortgages

Credit Losses Hurt Bank Earnings

An Initial Economic Shock

4 complexity and dark risk
4. Complexity and Dark Risk

Complexity

Limited Data

Dark Risk

+

5 alternate means of valuation
5. Alternate Means of Valuation

Old Credit Risk Mantra

What is the second means of repayment?

Proposed Capital Markets Mantra

What is the second means of valuation?

5 alternate means of valuation3
5. Alternate Means of Valuation

IRS

CDS

Corporate CDOs (2006)

Subprime CDOs (2006)

Ease of Current Valuation

Level 1

Observable prices in active markets

Observable prices in inactive markets or observable inputs to accepted pricing models

Level 2

Few or no observable market prices and models requiring significant unobservable inputs

Level 3

5 alternate means of valuation4
5. Alternate Means of Valuation

Effectiveness of Alternate Means of Valuation

Level 2

Level 3

Level ?

Level ?

IRS

Corporate CDOs (2006)

Subprime CDOs (2006)

CDS (2006)

Level 1

Ease of Current Valuation

CDS (2008)

Level 2

Corporate CDOs (2008)

Level 3

Subprime CDOs (2008)

estimated us banks balance sheet 2008 q2
Estimated US Banks Balance Sheet (2008 Q2)

Subprime Related

$540 Bill

$11,950 Bill

L i a b i l i t i e s

A l l O t h e r A s s e t s

$12,761 Bill

Equity

Subprime Related Assets

?

Equity

$1,351 Bill

a question
A Question

Was this crisis a Black Swan?

?

slide30

Elements of the Risk Puzzle (Original: May 2006)

Technological Change

Pace of Innovation

Product Complexity

Geopolitical Risk

Liquidity

Model Risk

Commodity Prices

Extreme Events

Volume Growth

External Linkages

Emerging Markets

Information Security

Operational Risk

Effective Portfolio Mgt.

Regulatory Uncertainty

Miscellaneous

???? Unknown Unknowns ????

slide31

Elements of the Risk Puzzle (Rev: October 2008)

Pace of Innovation

Product Complexity

Technological Change

Pace of Innovation

Product Complexity

Liquidity

Model Risk

Geopolitical Risk

Liquidity

Model Risk

Volume Growth

Commodity Prices

Extreme Events

Volume Growth

External Linkages

External Linkages

Emerging Markets

Information Security

Operational Risk

Effective Portfolio Mgt.

Regulatory Uncertainty

Miscellaneous

???? Unknown Unknowns ????

Commodity Prices

Effective Portfolio Mgt.

summary
Summary

1. Statistical Entropy

2. Structural Imagination

Data

Information

  • Use structural imagination to define significant unrepresented variables in existing risk analysis
  • Track these variables as early warning indicators
summary1
Summary

CompoundEconomic Impact

3. Self-Referential Feedback

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

summary2
Summary

4. Complexity  Dark Risk

  • Limited data and untested complexity make risk estimates inherently uncertain
summary3
Summary

5. Second Means of Valuation

?

Limit holdings of assets with no reasonably objective second means of valuation even if they are highly liquid today

a final thought strategic risk
A Final Thought – Strategic Risk

Board of Directors

Where the buck stops

CEO

“Give me 15% more than last year. Don’t give me excuses, give me the numbers.”

≠ sound aggressive management

= recipe for disaster

ad