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1 Innovation, Change, Black Swans, and Financial Crises David Marshall* Senior Vice President Federal Reserve Bank of Chicago PhD Project Finance Doctoral.

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Presentation on theme: "1 Innovation, Change, Black Swans, and Financial Crises David Marshall* Senior Vice President Federal Reserve Bank of Chicago PhD Project Finance Doctoral."— Presentation transcript:

1 1 Innovation, Change, Black Swans, and Financial Crises David Marshall* Senior Vice President Federal Reserve Bank of Chicago PhD Project Finance Doctoral Students Association Conference Santa Fe, NM June 19, 2011 * The opinions in this presentation are the presenter’s and do not reflect positions of the Federal Reserve Bank of Chicago or the Federal Reserve System.

2 2 Change as a factor in financial crises Innovation and change –Shifts the distribution of key random variables –“Black Swan” events –Can disrupt risk management Distributional change from 2000 to 2008 –The Great Moderation –Capital flows into U.S. –Subprime mortgage contracts How these changes were instrumental in the Crisis of 2008

3 3 Historical record Financial crises often associated with innovation and change Examples: –Penn Central crisis of 1970  Innovation: commercial paper –1987 stock market crash  Innovation: computerized program trading/portfolio insurance –1998 LTCM crisis  Innovation: highly leveraged hedge funds

4 4 Why is change associated with crises? Essential to all finance practice: ability to quantify risk –Estimate a probability distribution using data from the past, Suppose something completely new happens –Shifts the distribution of relevant random variables –Distributional shift poorly understood in real time –Prevailing wisdom: old distribution still applies Distributional shifts of this type not captured in most economic models currently in use –Rational expectations models, regime shifting models, models with learning, behavioral models  All assume an unchanging distribution or meta-distribution

5 5

6 6 “Black Swans” Black Swans –Tail events thought to be virtually impossible (under the old distribution) actually occur When the Black Swan event occurs, –Market participants exposed to unforeseen risks –No reliable distribution to use in managing risks Shift from –Statistical control (maximize risk-adjusted return) to –Robust control (avoid the worst-case outcome)  Withdraw from risks, “flight to quality”  Financial crisis.

7 7 The distribution before the crisis The Great Moderation –Virtually unprecedented period of low macroeconomic volatility –Only two extremely mild recessions –Otherwise, 2% - 4% y-o-y GDP growth Why? –New household finance instruments  Home equity credit lines, cash-out refinancing  Allows households to smooth consumption –More sophisticated derivative instruments  Allows for improved risk sharing –Better conduct of monetary policy

8 8 Change in real GDP (year-over-year)

9 9 The distribution before the crisis The Great Moderation –Virtually unprecedented period of low macroeconomic volatility –Only two extremely mild recessions –Otherwise, 2% - 4% y-o-y GDP growth Why? –New household finance instruments  Home equity credit lines, cash-out refinancing  Allows households to smooth consumption –More sophisticated derivative instruments  Allows for improved risk sharing –Better conduct of monetary policy

10 10 What shifted the distribution? Massive capital flows from abroad into U.S. markets –By 2006, 6 ½ % of GDP –Induced very low real interest rates –Rising home prices Innovation: Subprime mortgages –High loan-to-income ratios –Low borrower credit scores –Very low down payments –Substantial upward rate adjustment in two or three years –Bet on continued house price appreciation –Government policy: Expand use of subprime mortgages –By 2006, subprime/Alt-A mortgage issuance ≈ 30% of the mortgage market

11 11 Flow of capital into U.S. and real interest rates

12 12 Housing price index 1987-present

13 13 What shifted the distribution? Massive capital flows from abroad into U.S. markets –By 2006, 6 ½ % of GDP –Induced very low real interest rates –Rising home prices Innovation: Subprime mortgages –High loan-to-income ratios –Low borrower credit scores –Very low down payments –Substantial upward rate adjustment in two or three years –Bet on continued house price appreciation –Government policy: Expand use of subprime mortgages –By 2006, subprime/Alt-A mortgage issuance ≈ 30% of the mortgage market

14 14 What shifted the distribution? (continued) Mortgage Backed Securities (MBS) –Cash flow from a pool of mortgages paid to investors –Senior (AAA) tranches get first claim to cash flow –Equity tranches protect senior tranches by absorbing first losses –Only works if defaults within the mortgage pool have low correlation! Old Distribution –Great Moderation – low risk environment –Mortgage defaults idiosyncratic –House price declines geographically localized –Nationwide major home price declines virtually impossible –Default risk diversified away through the MBS structure As long as house prices continued to rise, subprime default rate was low –Old distribution seemed to work

15 15 What shifted the distribution? (continued) Problem: Subprime mortgage contracts are especially sensitive to house price declines, –Little or no equity cushion –If prices decline, the mortgage is underwater and the borrower is likely to default. So a nationwide decline in housing prices would trigger correlated defaults within the mortgage pool underlying subprime MBSs. –AAA tranches of subprime MBSs no longer protected by equity tranches! –Subprime MBSs were ticking time bombs –Key shift in the returns distribution not perceived in real time! When house prices started to decline in mid-2006, subprime mortgages started to default more rapidly than predicted by old distribution.

16 16 Subprime defaults

17 17 S&P ratings transition matrix pre-crisis

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19 19 Recap Periods of change –New innovations, structures, policies –Effect on the distribution of returns initially not well understood –Market participants can’t quantify risk –Best strategy: Shift to robust control  Avoid worst case outcome  Avoid markets where risk can’t be quantified  Flight to quality  Liquidity flows attenuate or cease entirely   Financial crisis Pace of change in the future will likely accelerate. –Higher likelihood of financial crises in the future Best policy: Create a more robust financial structure that can better withstand the inevitable crises that will occur


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