1. Deciphering the 2007/8 Liquidity
and Credit Crunch
Markus K. Brunnermeier
Princeton University
Written notes will be available at
http://www.princeton.edu/~markus
1

2. Overview of Talk
Run-up
1.
Creation of structured products
Demand for structured products
Consequences: Buy-out bonanza, house price frenzy
Unfolding of crisis
2.
Subprime, ABCP, banking crisis
Quant crisis
Mechanisms at work
3.
Difference to previous crises
4.
2

3. 1.1 Creation of Structured Products
Bond Thickness “Loss
Securitization I
Tranches Support”
Insuring CDS
AAA 80% 20%
US$ ≈45tr (corporate debt ≈5tr)
Pooling AA 5% 15%
Tranching CDOs A 5% 10%
Catering
BBB+ 2% 8%
Opaqueness
BBB 1% 7%
Securitization II
BBB- 2% 5%
Shortening maturity SIVs et al.
BB 1% 4%
Traditional business of banks
“Ride yield curve” Overcollateralization 4% 0%
(Equity)
Buy long-term assets
Sell and roll over
short-term assets (ABCP)
Opaqueness in off-balance sheet
vehicles
3

4. 1.2 Shortening Maturity - SIVs et al.
Conduits SIVs SIV-lites
US$ ≈1,400bn US$ ≈400bn US$ ≈12bn
assets
not tradable loans assets are traded assets are traded
less risky less risky risky
RMBS 43% fin. Inst. Debt >95% US RMBS
•≈11% •≈ •
•≈11% ABS/CDOs •≈ 23% RMBS
•≈ 11% CDOs
26% ABCP
liabilities
68% MTN
7% capital/mez.notes
non-structured structured structured (aggressively)
capital structure
open closed
dynamic (change size/financing) static (like CDOs)
Some No (but overcollateralized) No
Credit
(sponsoring bank)
enhancement
Contractual Contractual Contractual
Liquidity enhanc.
100% < outstanding ABCP credit line is subject
(credit line) 4
to market value tests
Reputational

5. 1.3 Why Structured Products?
Good reasons
Catering – transfer risk who can best bear it –
stayed mostly within banking system
(complete markets)
Bad reasons
Supply:
Rating Arbitrage – Diluting existing bond holders
Transfer highly rated asset to SIV and issue AAA papers
Instead of issuing A- minus rated papers
+ banks’ rating was unaffected by this practice
Regulatory Arbitrage: Outmaneuver Basel I accord (SIVs)
esp. reputational liquidity enhancements
Demand:
Creative way to enhance portfolio returns
searching for yield
track record building - picking up nickels before the steamroller
Attraction of illiquidity (no price exists)
+ difficulty to value CDOs (correlation risk)
“mark-to-model”: Mark “up”, but not “down”
smooth volatility and increase Sharpe ratio
fraction of “level 3 assets” went up a lot
5

6. 1.4 Consequences of
“originate and distribute banking model”
Banks focus only on “pipeline risk”
Distance between borrowers and lenders
Opaqueness - obfuscation
Deterioration of lending standards
Mortgages
Mortgage brokers
Piggyback mortgages, NINJA loans, …
Housing Frenzy
Corporate bonds
Pik bonds
Covenant-lite bonds
Private equity bonanza – LBO acquisition spree
6

7. 2. Unfolding of Crisis
Subprime
1.
ABCP, banking crisis
2.
Spillover to corporate credit
3.
Quant crisis
4.
7

8. 2.1 Subprime crisis – envelope calculation
Subprime mortgage: 15% of US$ 10tr = US$ 1.5tr
Say: 50 % default, only recoup 50%
Total loss: US$ 375bn, incl. Alt-A say, US$ 500bn
2% change in stock market > US$ 500bn Amplifying mechanism
needed 8

9. 2.2 ABCP – Banking Crisis
Rates
Outstanding ABCP 6.5
1300
6
1200
1100 5.5
1000 5
900 4.5
800 4
ABCP
700
3.5
A B CP
LIBOR 3 months
FinCP
T-Bill 3 months
FedFund
600
3
7
7
7
7
7
7
7
7
/0
/0
/0
/0
/0
/0
0
0
8/
5/
27
11
25
22
19
/3
07
07
07
07
07
7
7
7
7
7
7
7
7
7
7
/0
/0
/0
/0
/0
/0
/0
/0
/0
/0
8/
9/
10
1/
8/
5/
2/
9/
6/
7/
7/
8/
9/
15
22
29
12
19
26
16
23
30
/7
7/
7/
8/
9/
9/
10
7/
7/
7/
8/
8/
8/
9/
9/
9/
ABCP dries up – no rollover
SIVs draw on credit lines of sponsoring bank
LIBOR and flight to quality
Banking Crisis: IKB, SachenLB, Northern Rock
9

10. 2.3 Spillover to Corporate Credit
600 3000
500 2500
400 2000
300 1500
200 1000
Note difference in scale!
100 500
CDX.HY.5y On the Run ABX.HE.BBB- On the Run
0 0
07
07 07 07
7 07 07 07 07 07
/0 1/
1/ 1/ 1/ 1/ 1/ 1/
1/ 1/
1
0/
1/ 2/ 3/ 4/ 5/ 6/ 7/ 8/ 9/ 1
Novelty effect
Learning about structured products
10

11. 2.4 Quant Crisis
High frequency stat arbs
1.
High frequency, IT driven, short-term reversal
strategies
Aug 1st to Aug 9th - price declines seven days in a row
e.g. Renaissance’s Medallion fund
Low frequency quant funds
2.
Value-growth (HML) strategy, momentum strategy
FX carry trades
e.g. Goldman Sachs’ Global Alpha, AQR, …
11

12. 2.4 Quant Crisis
Funds’ assets in general
(Knowledge) Market Order of
Acquisition Cost Liquidity Liquidation
High fixed costs Low/High 3
Proprietary trading
strategy
(incl. credit)
Low cost High 2
Standard trading
strategy
(incl. carry trade, HML)
No cost 1
∞
Cash holding
12

13. 2.4 Quant Crisis
HML Accumulative Returns Deutsche Bank Carry Trade ETF
1.02
1.18
1 1.16
1.14
0.98
1.12
0.96 1.1
1.08
0.94
1.06
0.92
1.04
1.02
0.9
1
0.88
0.98
07
07
07
07
07
07
07
07
07
07
07
07
07
07
07
07
07
07
20
20
20
20
20
20
20
20
20
20
20
20
20
20
20
20
20
20
1/
1/
1/
1/
1/
1/
1/
1/
1/
1/
1/
1/
1/
1/
1/
1/
1/
1/
3/
4/
5/
6/
7/
8/
9/
1/
2/
Date
1/
2/
3/
4/
5/
6/
7/
8/
9/
Date
Why? Many (not only quant) funds liquidate “relatively”
liquid positions first
Quant funds are particularly loaded on these factors
13

14. Cumulative Return
6/
1/
20
85
90
95
100
105
07
6/
8/
20
07
6/
15
/2
00
7
6/
22
/2
00
7
6/
29
/2
00
7
7/
6/
20
07
Daily HFR indexes
7/
13
/2
2.4 Quant Crisis
00
7
7/
Equity Market Neutral Index
Stat arb crisis
20
/2
00
7
7/
27
/2
00
7
8/
3/
20
07
8/
10
Macro Index
/2
00
7
8/
17
/2
00
7
8/
24
/2
00
7
8/
31
/2
Global Index
00
7
HFR indexes
14

15. 3. Mechanisms
Market liquidity
Ease with which one can raise money
by selling the asset
Funding liquidity
Ease with which one can raise money
by borrowing using the asset as collateral
Each asset has two values/prices
1. price
2. collateral value
15

16. 3. The 3 Flavors of (the same)
Funding Liquidity Risk
Margin funding risk Prime broker
Margin has to be covered by HF’s own capital
Margins increase at times of crisis
Rollover risk CP
Inability to roll over short-term commercial paper
Redemption risk Depositors, HF-investors
Outflow of funds for HFs and banks
Essentially the same!
Maturity mismatch: Long-term assets but
short-term borrowing
16

17. 3. Mechanism 1
Collateral Crisis due to Increased Vol. + Losses
Permanent price shock is Rating Jan-May 2007 July-Aug 2007
accompanied by higher Bond
Investment grade 0-3 3-7
future volatility (e.g. ARCH) High yield 0-5 10+
Realization how difficult it is Leveraged Loan
to value structured products Senior 10-12 15-20
2nd lien 15-20 20-30
estimate default
Mezzanine 18-25 30+
correlations
ABS and CDO
Value-at-Risk shoots up AAA 2-4 8-10
AA 4-7 20
Margins/haircuts increase
A 8-15 30
Collateral value declines BBB 10-20 50
Funding liquidity dries up Equity 50 100
Source: Citigroup, IMF Stability report 2007
Liquidity/Margin Spiral
17

18. 3. Mechanism 1 - Margins for S&P 500 Futures
Collateral Crisis due to Increased Vol. + Losses
14%
12%
Black Monday
US/Iraq war LTCM
10/19/87
10%
8%
6%
4%
2%
1989 mini crash
Asian crisis
18
0%
Jan-82 Jan-84 Jan-86 Jan-88 Jan-90 Jan-92 Jan-94 Jan-96 Jan-98 Jan-00 Jan-02 Jan-04 Jan-06

19. 3. Mechanism 1 – Why ARCH?
Collateral Crisis due to Increased Vol. + Losses
vt = vt-1 + Δvt = vt-1 + σt εt
p1 σt+1= σ + θ |Δvt |
120
100
Λ
Λ
m1
80 m1
2
1 t
19

20. 3. Mechanism 1 – Hyperbolic Star
Collateral Crisis due to Increased Vol. + Losses
customers’
supply
_
x1 < W1/m1 = W1/(σ + θ|Δp1|)
20

21. 3. Mechanism 1
Collateral Crisis due to Increased Vol. + Losses
Liquidity spiral
Margin spiral (Redemption/roll-over spiral)
Loss spiral
Source: Brunnermeier & Pedersen (2007)
Both spirals reinforce each other
21

22. 3. Mechanism 2
Collateral Crisis due to Lemon’s Problem
Financiers are concerned
Collateral is more risky +
Receive a particular bad selection of collateral
Issuer knows best what’s in the pool of assets
Recall CDOs are particularly difficult to price
As margins/ABCP rate increase, selection
of collateral worsens
Leads to a further increase and
hence worse selection
ultimately leads to a market breakdown.
22

23. 3. Mechanism 3
Expertise, Complexity and Discreteness
CP stops to be viewed as “cash substitute”
Buyers of ABCP do not conduct a credit
analysis.
No expertise in credit quality evaluation
Deterioration in fundamentals makes credit
evaluation necessary
Withdrawal from ABCP market
Expertise is only slowly build up again
23

24. 3. Mechanism 4
Run on Financial Institutions
Run before others run – DYNAMIC
Financial Institutions
On Banks: Demand depositors, by withdrawing
On HFs: Prime brokers, by increasing margins
Investors, by redeeming funds
On SIVs: Investors, by not rolling over ABCP
Note:
“Liquidation policy” of SIVs favors early withdrawals!
24

25. 3. Mechanism 5
Gridlock Risk
Interweaved network of financial obligations
Lender and borrower at the same time
Example:
B
30m
50m
A 40m
60m
40m
C
30m
Gridlock, if A loses 30m – Deadlock, if A loses 55m
Opaqueness makes matters worse
Regulator can’t intervene 25
Warren Buffett is less likely to help out

26. 3. Mechanism 6
Precautionary Hoarding
“Funding cushion” for adverse events
increases for 3 reasons
SIVs might draw on credit lines
1.
Borrowing at interbank lending market is more
2.
volatile (since other banks might have SIV exposure)
Increased credit counterparty risk
3.
26

27. 3. Mechanism 7
Knightian Uncertainty
Market freezes up, since
Investors focus on worst-case analysis
if it is difficult to assign probabilities to different
outcomes (like value of CDOs)
Investors/banks hoard because they fear the
worst
27

28. 4. Differences to Previous Crisis
Common theme:
interaction between funding and market liquidity.
1987 crash: culprit was portfolio insurance trading
1994 mortgage crisis: primarily prepayment risk
1998 LTCM crisis: specific convergence spread arbitrage
trades were well known
e.g. on-the run and off-run spread (not much in 2007)
known main player which needed to be bailed out
2000 Internet bubble – role of analysts
2007 culprit:
rating agencies
housing market correction
maturity mismatch
28

29. 5. Conclusion
Crisis with traditional elements:
due to mismatch of maturities
Interaction between funding and market liquidity
New level of opaqueness
Structured products are difficult to value
off-balance sheet vehicles (SIVs)
(Basel accord)
Several mechanism/“liquidity spirals” are at work
Collateral crisis due to increased volatility
Run on financial institutions (dynamic)
Gridlock risk
Hoarding 29