financial innovation and default rates samuel maurer hoai-luu nguyen asani sarkar jason wei january...
TRANSCRIPT
Financial Innovation and Default Rates
Samuel MaurerHoai-Luu Nguyen
Asani SarkarJason Wei
January 2, 2009
DAY AHEAD CONFERENCE 2009, SAN FRANCISCO
These views belong to the authors, and do not necessarily those of the Federal Reserve Bank of New York or the Federal Reserve System.
2
Motivation
• Measured default rates have been unusually low relative to history and economists’ predictions
Moody's Global Speculative Grade Forecasts
0.01
0.02
0.03
0.04
Jan-0
7
Mar-
07
May
-07
Jul-0
7
Sep-0
7
Nov-07
Jan-0
8
Mar-
08
May
-08
Jul-0
8
Sep-0
8
Nov-08
Def
ault
rat
e (%
)
Moody_dec06 Moody_mar Moody_may Moody_jun
Moody_jul Moody_oct global_spec
3
Why Models Over-Predicted Defaults
• Business cycle (not properly accounted for in models)
• Structural Break in default model relationships
• Omitted variable in default prediction model: financing
• Expanded menu of financing for distressed firms since 2004
– Traditional financing (bank loans; CP issuance)
– Structured financing (High-yield CLO, CDO issuances)• Rescue financing for distressed firms without access to traditional
financing• Substitute loans for bonds, increasing flexibility
– Structured financing vehicles (CLO managers)• Bring in new sources of capital• Major buyers of leveraged loans
4
Growth in Traditional Financing
0
50,000
100,000
150,000
200,000
250,000
90 92 94 96 98 00 02 04 06
CP_ISS
500,000
600,000
700,000
800,000
900,000
1,000,000
1,100,000
90 92 94 96 98 00 02 04 06
CILOAN_OUT
0E+00
1E+10
2E+10
3E+10
4E+10
5E+10
90 92 94 96 98 00 02 04 06
HY_ISS
5
Growth in Structured Financing
CDO Issuance: 1995-2006
0100200300400500600
1995
1997
1999
2001
2003
2005
Year
CD
O is
suan
ce (
$b)
All CDO Issuance
Global Leveraged Loan CLO Issuance
0
50
100
150
1995
1996
1997
1998
1999
2000
2001
2002
2003
2004
2005
2006
2007
In $
Bil
lion
Leveraged Loan CLO
6
Implications for Default Rates• Default delayed or avoided, depending on investment opportunities
• Structural model: Default occurs if firm value V below a threshold V*
– Financing may increase V (no change in recovery rates) or
– Lower V* (lower recovery), perhaps due to the greater flexibility of leveraged loans compared to traditional financing (e.g. less covenants or PIK terms)
Standard Merton-type Framework
0
20
40
60
80
100
120
140
160
1 5 9 13 17 21 25 29 33 37 41 45 49 53 57 61 65 69 73 77 81 85 89 93 97
Time
Fir
m V
alu
e as
Pct
of
So
lven
cy L
evel
Path A Path B High Threshold Low Threshold
7
The Number of Covenants had been on the Decline
Mean Number of Covenants Per Contract - Senior Unsecured Debt
0
1
2
3
4
5
6
7
8
9
10
11
1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007
Offering Year
No
. of
Co
ven
ants
Speculative Grade
Investment Grade
8
Analysis: Financing and Default Rates
• Year-rating-cohort analysis: Is there a reduction in the proportion of bonds defaulting early?
• Prediction model for monthly aggregate default rates– Evidence of structural break in most recent sample
• Structured financing, distance to default and default rates
• Traditional financing, distance to default and default rates
9
Results
• Evidence is consistent with “delayed defaults”– Proportion of early defaults are historically low
• Evidence of structural break in most recent sample
• Financing measures significantly related to distance to default and default rates
10
Contributions• Empirically link default rates to financing
– A new channel for endogenous default boundary (flexibility of loan terms)– Chen (2007): simultaneously determines firm’s capital structure and default
decisions– Rajan, Seru, Vig (2008): Mortgage models under-predicted defaults in
recent years due to lowered incentive to monitor– Mian and Sufi (2008): expansion of mortgage supply led to defaults– Keys et al (2008): securitization reduces screening by lenders– Leland and Toft (1996), Anderson, Sundaresan, Tychon (1996):
endogenizes default boundary
• New channel for financial innovations to affect the economy– Lower long-run default rates by reducing the compensation required for
bearing credit risk• Spread credit risk to less risk-averse investors• Reduce macroeconomic and financial volatility
– May have delayed bankruptcy in the short-run by making more distress financing available and on better terms
11
Data
• Moody’s data on annual cumulative default rates by yearly cohort for speculative-grade issuers, 1980-2006
• 3 ways to default– Missed/delayed payment of principal/interest– Legal blocks to timely payment (e.g. bankruptcy)– Distressed exchange
• Cumulative issuer-weighted default rates at the end of year, for bonds outstanding as of the beginning of the year
14
Predicting Monthly Default Rates
Outcome variable: Changes in the default rate
Moody default rates: trailing 12-month rates
Change in rates potentially affected by default events up to 12 month past
• Calls for including several lags of explanatory variables
15
Determinants of Default Rate (All Variables in Changes)
12*
12*)*5.0()/( 2
ttt
LVLnDdefault
• Distance to Default• Number of standard deviations of asset growth by which the asset level > firm’s liabilities
V: firm value; L: liability measure (st debt + 0.5*lt debt)
μ: mean asset growth σ: standard dev of asset growth
• Macro conditions•10 year – 3 month term spread•Unemployment rates •Consumer expectations
• Credit quality •High yield – IG credit spreads
• Stock returns
16
Results Distance to default Macroeconomic
Conditions Credit Quality and
Stock Returns Growth in Corporate
Leverage Explanatory Variable
Estimate t-stats Estimate t-stats Estimate t-stats Estimate t-stats
Dependent variable: D Intercept -0.02 -0.71 -0.02 -0.86 -0.06 ** -2.53 -0.09** -2.50
DDEF, Lag1 0.36 1.34 0.18 0.57 0.50* 1.86 0.52* 1.81
TERM, Lag12 --- --- -0.17** -2.10 -0.18** -2.15 -0.16* -1.83
CON EXP , Lag1 --- --- -0.01* -1.88 -0.01* -1.70 -0.01* -1.77 LEV_GR , Lag1 --- --- --- --- --- --- 0.01 1.06
VARIABLES WITH MULTIPLE LAGS UEM, 3 Lags
+, SIG --- 1 1 2 -, SIG 0 0 0
CQ, 10 Lags +, SIG --- --- 6 6 -, SIG 0 0
SRET, 6 Lags +, SIG --- --- 3 2 -, SIG 0 0 12 Lags of DEF?D included?
YES YES
YES YES
Adj -R2 0.38 0.41 0.48 0.48
18
Stability Tests
• Has historical relationship between default rates and fundamentals changed?
• Statistical break tests: evidence of a break in 2003– Factor breakpoint test (10% significance)– CUSUM test (5% significance)
• No further breaks in sample from 2004
19
Distance to Default and Financing
Standard Merton-type Framework
0
20
40
60
80
100
120
140
160
1 5 9 13 17 21 25 29 33 37 41 45 49 53 57 61 65 69 73 77 81 85 89 93 97
Time
Fir
m V
alu
e as
Pct
of
So
lven
cy L
evel
Path A Path B High Threshold Low Threshold
20
Distance to Default and Structured Financing: Results
Growth in high-yield CLO issuance
Growth in aggregate CDO
issuance Explanatory Variable
Estimate t-stats Estimate t-stats
Dependent variable: ∆ DDEF Intercept 0.53 0.89 0.29 0.84 LL_GR, Lag1 0.37 0.86 --- --- LL_GR, Lag2 0.46** 2.36 --- --- LL_GR, Lag3 0.05** 4.15 --- --- LL_GR, Lag4 0.04** 3.85 --- ---
CDO_GR, Lag1 --- --- 0.94* 2.03 CDO_GR, Lag2 --- --- 0.86** 4.69 CDO_GR, Lag3 --- --- 0.67** 2.98 2 Lags of ∆ DDEF included?
YES YES
Wald test: All lags of financial innovation are zero Chi-sq p-value 0.00 0.00 Adj-R2 0.91 0.93
21
Distance to Default and Traditional Financing: Results
CP Issuance C&I Loans DDEF DDEF Explanatory Variable
Estimate t-stats Estimate t-stats
Intercept 1.61** 3.43 4.24 -0.08** ∆DDEF: Fitted, Lag1 --- --- --- 0.52**
∆DDEF: Resid, Lag1 --- --- --- -1.90* CP_GR, Lag1 2.29 0.46 --- --- CP_GR, Lag2 3.19 0.55 --- --- CP_GR, Lag3 -0.86 -0.17 --- --- CP_GR, Lag4 -4.58 -1.04 --- --- CP_GR, Lag5 -7.76** -2.42 --- --- CP_GR, Lag6 -5.79* -1.99 --- --- CIL_GR, Lag1 --- --- -29.00 -0.88 CIL_GR, Lag2 --- --- -27.94 -0.77 CIL_GR, Lag3 --- --- -76.01** -2.62 CIL_GR, Lag4 --- --- -30.81 -1.13 CIL_GR, Lag5 --- --- -45.53* -1.98 OTHER CONTROLS INCLUDED? YES YES
All lags=0? Chi-sq p-value 0.02 0.03
Sum of lags=0? Chi-sq p-value 0.38 0.03 Adj-R2 0.90 0.91
22
Financing and Default Rates
• Two channels
• Indirect: Effect on defaults via its effect on default boundary– Fitted DDEF: part explained by financing– Residual DDEF: part orthogonal to financing
• Direct
23
Structured Financing and Default Rates
No financing Growth in high-yield CLO issuance
Growth in CDO issuance
Explanatory Variable
Estimate t-stats Estimate t-stats Estimate t-stats
Intercept -0.08** -2.62 -0.04 -1.60 -0.01 -0.54 ∆DDEF: Fitted, Lag1 0.41* 1.75 0.29* 2.03 1.08** 4.73
∆DDEF: Resid, Lag1 -1.60* -1.93 -1.10* -1.81 -2.60** -2.42 LL_GR, Lag1 --- --- -0.04** -2.75 --- --- LL_GR, Lag2 --- --- 0.01 1.21 --- --- LL_GR, Lag3 --- --- 0.05** 3.96 --- --- LL_GR, Lag4 --- --- -0.00** -2.48 --- --- CDO_GR, Lag1 --- --- --- --- -0.07** -3.89 CDO_GR, Lag2 --- --- --- --- 0.02 0.83 CDO_GR, Lag3 --- --- --- --- -0.01 -0.63 CDO_GR, Lag4 --- --- --- --- -0.04* -2.55 CDO_GR, Lag5 --- --- --- --- -0.08** -3.93 CDO_GR, Lag6 --- --- --- --- -0.04** -2.41 SRET,Lag1 -0.48 -0.44 -1.95** -3.32 -1.81** -2.79 OTHER CONTROLS INCLUDED? YES YES YES Walt test: All lags of financial innovation are jointly zero Chi-sq p-value --- 0.00 0.00 Walt test: Sum of all lags of financial innovation is zero Chi-sq p-value --- 0.59 0.00 Adj-R2 0.24 0.65 0.61
24
Traditional Financing and Default Rates, 2005-2007
Explanatory Variable
Est. t-stats Estimate t-stats
Intercept -0.11** -2.95 -0.08** -3.12 ∆DDEF: Fitted, Lag1
0.53** 3.79 0.52** 2.09
∆DDEF: Resid, Lag1 -1.89** -2.86 -1.90* -2.05 CP_GR, Lag1 0.16 0.83 --- --- CP_GR, Lag2 0.40** 2.18 --- --- CP_GR, Lag3 0.23 1.47 --- --- CP_GR, Lag4 0.07 0.37 --- --- CP_GR, Lag5 -0.21 -1.27 --- --- CP_GR, Lag6 -0.24* -1.91 --- --- CIL_GR, Lag1 --- --- 0.43 0.48 OTHER CONTROLS INCLUDED? YES YES All lags=0? Chi-sq p-value 0.00 0.48 Sum of all lags=0? Chi-sq p-value 0.47 0.48 Adj-R2 0.35 0.23
25
Conclusions
• Proportion of early defaults are historically low– Consistent with “delayed defaults” (since defaults are now
already turning up)
• Structural break in recent sample, coincides with period of rapid growth in financing
• Including finance in prediction model is informative– Significantly related to distance to default– Component of distance to default explained by financing
positively related to defaults– Residual component negatively related to defaults