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What Have We Learned from the Sub Prime Crisis? Professor Anthony Saunders John M. Schiff Professor of Finance New York University Stern School of Business.

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Presentation on theme: "What Have We Learned from the Sub Prime Crisis? Professor Anthony Saunders John M. Schiff Professor of Finance New York University Stern School of Business."— Presentation transcript:

1 What Have We Learned from the Sub Prime Crisis? Professor Anthony Saunders John M. Schiff Professor of Finance New York University Stern School of Business May 2008

2 2 How did we get here? Traditional Banking Traditional Banking –Banks as Delegated Monitors Disintermediation Disintermediation –Securitization Traditional SPV-based (special purpose vehicle) Traditional SPV-based (special purpose vehicle) SIV-based (special investment vehicle) SIV-based (special investment vehicle) –Syndication Back to the Future Back to the Future –Off-Balance Sheet Proprietary Investing –What happens when the delegated monitor delegates?

3 3 Getting here: Traditional Banks as Delegated Monitors The Traditional Bank – Delegated Monitoring Bank AssetsLiabilities Cash AssetsDeposits Purchased Funds Loans Capital

4 4 Getting Here: Traditional Securitization Securitization allowed banks to remove risk from their balance sheets Securitization allowed banks to remove risk from their balance sheets Securitization allowed banks to avoid onerous capital requirements Securitization allowed banks to avoid onerous capital requirements Securitization turned banks into underwriters – originate the loans and then sell them off. Securitization turned banks into underwriters – originate the loans and then sell them off.

5 5 The Traditional Securitization Process Bank AssetsLiabilities Cash AssetsDeposits Purchased Funds Loans SPV AssetsLiabilities LoansAsset-Backed Securities Investors Cash Loans Cash Capital

6 6 Getting Here: Asset-Backed Securities (ABS) and Decline in Quality of Underlying Assets Mortgage-Backed Securities (MBS) Mortgage-Backed Securities (MBS) –Residential MBS Pass-throughs and Collateralized Mortgage Obligations (CMOs) Pass-throughs and Collateralized Mortgage Obligations (CMOs) Subprime and No/Low Documentation Subprime and No/Low Documentation –Def. Subprime (2001 Interagency Expanded Guidance):  ≥Two 30-day delinquencies in last 12 mos. or ≥one 60- day delinquency in last 24 mo.; OR  Judgment, charge-off. foreclosure, repossession in last 24 mos.; OR  Bankruptcy in last 5 yrs; OR  FICO score ≤660; OR  Debt service/income ratio ≥50% Second Lien Mortgages (High Loan/Value Ratios) Second Lien Mortgages (High Loan/Value Ratios) Collateralized Debt Obligations (CDOs) Collateralized Debt Obligations (CDOs) –Cash CDOs and Synthetic CDOs Collateralized Loan Obligations (CLOs) Collateralized Loan Obligations (CLOs) Covenant Lite and PIK (payment in kind) Covenant Lite and PIK (payment in kind)

7 7 Source: Bank of England, Financial Stability Report, October 2007, Issue 22, page 6

8 8. Source: Loan Pricing Corporation website

9 9 Getting Here: Loan Syndication Banks as underwriters Banks as underwriters –Firm Commitment (Underwritten) deals: The lead bank commits to making the loan in its entirety and then assembles participants to reduce its own loan exposure. Thus, the borrower is guaranteed the full face value of the loan. –Best Efforts deals: The size of the loan is determined by the commitments of banks that agree to participate in the syndication. The borrower is not guaranteed the full face value of the loan. –Club deals: For small deals (usually $200 million or less), the loan is shared among banks, each of which has had a prior lending relationship with the borrower. Leveraged Loan Syndications Leveraged Loan Syndications –Below investment grade –Often, they will have debt to cash flow levels in excess of 4:1 (i.e., their outstanding indebtedness (i.e., face value of debt) is more than four times the borrowing firm’s annual revenues) –Decline in Quality of Loan Syndications.

10 10 Syndicated Lending Borrower Bank (Syndicate Lender) Syndicate Member Syndicate Member Syndicate Member

11 11 Source: Loan Pricing Corporation website.

12 12 Getting Here: SIVs Banks as underwriters Banks as underwriters –Switching from spreads to fees –Reduce risk, but reduce return –Response: A new form of intermediation – back to the future of SIVs. –Formula for disaster: SIV = Traditional Bank – Regulatory Oversight SIV = Traditional Bank – Regulatory Oversight SIVs are exposed to traditional banking risks: interest rate risk, liquidity risk, credit risk SIVs are exposed to traditional banking risks: interest rate risk, liquidity risk, credit risk

13 13 A New Securitization Process Bank AssetsLiabilities Cash AssetsDeposits Purchased Funds Loans SIV AssetsLiabilities LoansCommercial Paper Investors Cash Loans Cash Capital ABCP

14 14 Getting Here: Proprietary Investing Banks establish hedge funds, private equity funds, venture funds through equity investing and/or lending. Banks establish hedge funds, private equity funds, venture funds through equity investing and/or lending. Unregulated activities conducted off the bank’s balance sheet. Unregulated activities conducted off the bank’s balance sheet.

15 15 Anatomy of the Storm and Credit Risk Models Can we have higher return without higher risk? Can we have higher return without higher risk? –Why did Credit Risk Measurement Models fail? –Which risks were underestimated?

16 16 Anatomy of the Storm: The Phases of the Crisis – Bank of England

17 17 Phase 1: Anatomy of the Storm: Assumption of Perpetually Rising US House Prices Subprime and “teaser” rate mortgages depend on rising housing prices to: Subprime and “teaser” rate mortgages depend on rising housing prices to: –Refinance upon hitting expiration of introductory teaser rate. But, there is a strong correlation between PD and level of rates (see, Stiglitz and Weiss) –Sale of property in the event of borrower’s inability to make payments. If housing prices increase, Loss Given Default = 0 –Both PD and LGD exhibit “procyclicality” –Thus underestimate PD, LGD and ρ (PD, interest rates).

18 18 Phase II of the Storm: Rising Spreads on RMBS Source: Bank of England, Financial Stability Report, October 2007, Issue 22, page 7. Underestimate ρ (RMBS vs. RMBS EUR

19 19 Phase II: Higher spreads, lower prices, fewer MBS originations Underestimate ρ (AAA, BBB-)

20 20 Phase III of the Storm: The Crisis Spreads to Other ABS Markets CDO spreads increase CDO spreads increase CDO issuance declines CDO issuance declines Leveraged Loan prices fall Leveraged Loan prices fall

21 21 CDO Spreads Increase Source: Loan Pricing Corporation website. Underestimate ρ across debt markets, i.e., ρ (RMBS, CDOs)

22 22 Leveraged Loan Prices Fall Source: Leveraged Loan Index is the CSFB Leveraged Loan Index Plus Average Price, expressed as a percentage of par, Bloomberg Ticker = DLJLPX Underestimate ρ (RMBS, HLT)

23 23 Phase IV: Risk Flows Back to Banks – Reintermediation SIVs are unable to issue Asset-Backed Commercial Paper SIVs are unable to issue Asset-Backed Commercial Paper SIVs access their backup lines of liquidity and take down credit lines SIVs access their backup lines of liquidity and take down credit lines Banks are unable to securitize or syndicate these loans due to the decreased volume of new deals Banks are unable to securitize or syndicate these loans due to the decreased volume of new deals Even if they could sell off these unwanted loans, the prices would be low as spreads increase. Even if they could sell off these unwanted loans, the prices would be low as spreads increase. SO: Banks did not really remove the risks from their balance sheets. SO: Banks did not really remove the risks from their balance sheets. Underestimate correlation between on and off-balance sheet risk, i.e., ρ (Risk on, Risk off) Underestimate correlation between on and off-balance sheet risk, i.e., ρ (Risk on, Risk off)

24 24 Phase V: Liquidity Hoarding and Flight to Quality Creates Mispricings Source: St. Louis Federal Reserve Bank database, FRED website. Underestimate ρ (credit risk, liquidity risk)

25 25 How do we steer out of the storm? Better Risk Modeling Better Risk Modeling –Price of risk was set too low in the mortgage market. –Quantity of risk was underestimated – the pitfalls of hidden leverage. –Improve credit rating models PD and LGD. –Analyze correlation across markets, risks and countries Align Incentives Align Incentives –What does it tell you when informed lenders treat their loans like hot potatoes? Avoid Regulatory Mispricings Avoid Regulatory Mispricings –Basel II implications

26 26 If capital is required: Standardized model risk weights: Standardized model risk weights: Credit Conversion Factor for Off-Balance Sheet Items: Credit Conversion Factor for Off-Balance Sheet Items: 100% unless “eligible liquidity facility” – limited draw-down privileges unrelated to default – then 50% CCF for maturity > 1 year and 20% CCF for maturity ≤ 1 year 100% unless “eligible liquidity facility” – limited draw-down privileges unrelated to default – then 50% CCF for maturity > 1 year and 20% CCF for maturity ≤ 1 year

27 27 Steering Out: Potential Pitfalls of the Basel II Securitization Requirements Places heavy reliance on external credit ratings. Places heavy reliance on external credit ratings. –Standardized model uses credit ratings –In the hierarchy of IRB approaches, RBA is preferred – tied to credit ratings What happens when the credit ratings are wrong? What happens when the credit ratings are wrong?


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