Annual Default Study - Financial Times · double edged sword but we’d still expect European...
50
Deutsche Bank Markets Research Global Credit HY Strategy IG Strategy Date 11 April 2016 Annual Default Study Past the Point of No Return? ________________________________________________________________________________________________________________ Deutsche Bank AG/London DISCLOSURES AND ANALYST CERTIFICATIONS ARE LOCATED IN APPENDIX 1. MCI (P) 057/04/2016. Jim Reid Strategist (+44) 20 754-72943 [email protected] Nick Burns, CFA Strategist (+44) 20 754-71970 [email protected] Michal Jezek Strategist (+44) 20 754-55012 [email protected] Sukanto Chanda Strategist (+44) 20 754-52461 [email protected] US Credit Strategy Oleg Melentyev, CFA Strategist (+1) 212 250-6779 [email protected] Daniel Sorid Strategist (+1) 212 250-1407 [email protected] Welcome to the 18 th annual edition of this report. In last year’s study we speculated how the next full default cycle could materialise in 2017-2018 with US Energy likely to go through a full cycle independently of the wider market moves. 12 months on and our late cycle fears continue to build. We continue to live in a low default world for now though. Even though defaults picked up in 2015, B/BB default rates were still comfortably below their long-term average which they have been for well over a decade now with 2009 being the only exception. Indeed last year’s default rate for global Bs (up from 0.9% to 2.7%) was still lower than all of the first two decades of the modern era of leveraged finance up to 2003. So in spite of all the challenges we face this era has been characterized by astonishingly low default rates. There are clear signs the cycle is turning though, especially in the US. Our US strategists have previously suggested that we need the combination of three conditions for us to be confident the next default cycle is imminent. We need the accumulation of excessive debt - preferably of deteriorating quality - an external shock/trigger and tighter monetary policy/flattening of yield curves. The pieces of the jigsaw are building. US corporate debt accumulation now compares with that seen prior to previous default cycles. Equity volatility has seen two spikes in the last year (August & early 2016), bank equity is falling (a lead indicator of lending?) and global yield curves continue to flatten. Europe remains more complicated. The near term risks of a sizeable default pick-up are low but a US/global led recession in 2017 or 2018 would change the outlook. For now ever aggressive ECB action is reducing the systemic risk in the market and in theory extending the artificial market for FI which should help corporates refinance when needed. However the stresses in European bank equity prices could also be a consequence of aggressive ECB policy (negative rates/yields) which could - if history is to be believed - reduce their appetite to lend and transmit the ECB’s policy throughout the region. So a possible double edged sword but we’d still expect European defaults to lag US. Overall the artificial ingredients continuing to keep defaults below their 1983- 2003 levels are still in place so the next default cycle could still be contained relative to the free market outcome and to the economic weakness. The Oil and Gas sector demonstrates that bad fundamentals can still win out though and our US strategists detail that the default risks might still not be priced in across this sector. Our current scenario analysis suggests annual US HY defaults around 9-11% by YE ‘17 and ’18 - 6-8% ex-Energy. For Europe it’s currently hard to see a peak above 5-7% in these years. This would be notably above current numbers but well below previous peaks. The good news is that spreads are not tight and adequately compensate buy- and-hold investors across the vast majority of historical default scenarios at a top-down level. This may not give mark-to-market investors any comfort when the next cycle hits but at least prices reflect some of the risks that are likely around the corner over the next two to three years.
Transcript of Annual Default Study - Financial Times · double edged sword but we’d still expect European...
Deutsche Bank Markets Research
Global
Credit HY Strategy IG Strategy
Date 11 April 2016
Annual Default Study
Past the Point of No Return?
________________________________________________________________________________________________________________
Deutsche Bank AG/London
DISCLOSURES AND ANALYST CERTIFICATIONS ARE LOCATED IN APPENDIX 1. MCI (P) 057/04/2016.
Jim Reid
Strategist
(+44) 20 754-72943
Nick Burns, CFA
Strategist
(+44) 20 754-71970
Michal Jezek
Strategist
(+44) 20 754-55012
Sukanto Chanda
Strategist
(+44) 20 754-52461
US Credit Strategy
Oleg Melentyev, CFA
Strategist
(+1) 212 250-6779
Daniel Sorid
Strategist
(+1) 212 250-1407
Welcome to the 18th annual edition of this report. In last year’s study we speculated how the next full default cycle could materialise in 2017-2018 with US Energy likely to go through a full cycle independently of the wider market moves. 12 months on and our late cycle fears continue to build.
We continue to live in a low default world for now though. Even though defaults picked up in 2015, B/BB default rates were still comfortably below their long-term average which they have been for well over a decade now with 2009 being the only exception. Indeed last year’s default rate for global Bs (up from 0.9% to 2.7%) was still lower than all of the first two decades of the modern era of leveraged finance up to 2003. So in spite of all the challenges we face this era has been characterized by astonishingly low default rates.
There are clear signs the cycle is turning though, especially in the US. Our US strategists have previously suggested that we need the combination of three conditions for us to be confident the next default cycle is imminent. We need the accumulation of excessive debt - preferably of deteriorating quality - an external shock/trigger and tighter monetary policy/flattening of yield curves. The pieces of the jigsaw are building. US corporate debt accumulation now compares with that seen prior to previous default cycles. Equity volatility has seen two spikes in the last year (August & early 2016), bank equity is falling (a lead indicator of lending?) and global yield curves continue to flatten.
Europe remains more complicated. The near term risks of a sizeable default pick-up are low but a US/global led recession in 2017 or 2018 would change the outlook. For now ever aggressive ECB action is reducing the systemic risk in the market and in theory extending the artificial market for FI which should help corporates refinance when needed. However the stresses in European bank equity prices could also be a consequence of aggressive ECB policy (negative rates/yields) which could - if history is to be believed - reduce their appetite to lend and transmit the ECB’s policy throughout the region. So a possible double edged sword but we’d still expect European defaults to lag US.
Overall the artificial ingredients continuing to keep defaults below their 1983-2003 levels are still in place so the next default cycle could still be contained relative to the free market outcome and to the economic weakness. The Oil and Gas sector demonstrates that bad fundamentals can still win out though and our US strategists detail that the default risks might still not be priced in across this sector. Our current scenario analysis suggests annual US HY defaults around 9-11% by YE ‘17 and ’18 - 6-8% ex-Energy. For Europe it’s currently hard to see a peak above 5-7% in these years. This would be notably above current numbers but well below previous peaks.
The good news is that spreads are not tight and adequately compensate buy-and-hold investors across the vast majority of historical default scenarios at a top-down level. This may not give mark-to-market investors any comfort when the next cycle hits but at least prices reflect some of the risks that are likely around the corner over the next two to three years.
11 April 2016
Annual Default Study: Past the Point of No Return?
Page 2 Deutsche Bank AG/London
Table Of Contents
One-Page Macro Section Summary .................................... 3
One-Page Default Analysis Summary ................................. 4
Past the Point of No Return? ............................................... 6 Stock and quality of HY debt .............................................................................. 6 Yield curve – A reliable indicator of future defaults .......................................... 10
US HY Default Rate Outlook ............................................. 16
US and European Default Rate Scenarios for 2017-2018 . 20
Long-Term US Default Model ........................................... 21
Historical Default Analysis ................................................ 23 Cohort analysis ................................................................................................. 23 Cohorts vs. current spreads .............................................................................. 23 Default-compensation spreads for broad cash and CDS indices ...................... 27 Spread implied default rates ............................................................................. 30
Appendix – Methodology, Raw Data and Calculations ..... 38 US vs. Europe cumulative default rates ............................................................ 38 How we calculate spreads required to compensate for default probability? .... 39 Recovery rates .................................................................................................. 40 Spreads required to compensate for default .................................................... 41 Credit trading levels against spreads required to compensate for default ........ 42
Why additional spread is required above that required to compensate for default ..................................................... 44
Market data as of COB 06 April 2016
11 April 2016
Annual Default Study: Past the Point of No Return?
Deutsche Bank AG/London Page 3
One-Page Macro Section Summary
We continue to live in a low default world. Even though 2015 showed signs of defaults picking up, BB/B default rates were still comfortably below their long-term average which they have been for well over a decade with 2009 the only exception. Indeed 2015’s default rate for global Bs (up from 0.9% to 2.7%) was still lower than all of the first two decades of the modern era of leveraged finance up to 2003. So in spite of all the challenges (too much debt and very low growth being the highlights), this era has been characterized by astonishingly low default rates.
Nevertheless there are clear signs the cycle is turning, especially in the US. Our US strategists have previously suggested that we need the combination of three conditions for us to be confident the next default cycle is imminent. We need the accumulation of excessive debt and preferably of deteriorating quality, some kind of external shock/trigger and tighter monetary policy/a flattening of the yield curve. The pieces of the jigsaw are building. US corporate debt accumulation now compares with that seen prior to previous default cycles. Equity volatility has seen two spikes in the last 12 months (August and early 2016), bank equity is falling (a lead indicator of lending?) and global yield curves continue to flatten.
In the note we expand on these themes. Interestingly the US yield curve which has been one of our main lead indicators for many years is still at a level that suggests a pick-up in defaults closer to averages rather than extremes. However it continues to flatten and global yield curves continue to keep the pressure on, especially in a world of ever increasing ECB and BoJ QE. At least the Fed seem to have relented for now which had they not could have led to a huge flattening of the curve. It could still continue but perhaps at a slower pace now.
The era of heavy financial repression and very active central banks might complicate default predictions even in a recession. Are we still in a period where default rates are likely to remain artificially suppressed even if we do see a full cycle? The artificial ingredients keeping defaults below their 1983-2003 levels are still broadly in place so the next default cycle could still be contained relative to the free market outcome and to the economic weakness although the Oil and Gas sector demonstrates that bad fundamentals can still win out and our US strategists detail that the default risks might still not be priced in across this sector, especially if the template from the TMT sector bust in the early 2000s is used. However for companies with more marginal default concerns, the artificial conditions in fixed income could still help prevent a more savage cycle.
Europe also remains a more complicated area when thinking about defaults. The near term risks of a pick-up are low but a US/global led recession in 2017 or 2018 would change the outlook. For now ever aggressive ECB action is reducing the systemic risk in the market and in theory extending the artificial market for FI which should help corporates refinance when needed. However the stresses in European bank equity prices could be a consequence of aggressive ECB policy (negative rates/yields) which could, if history is be believed, reduce their appetite to lend and transmit the ECB’s policy throughout the region. So a possible double edged sword but we’d still expect European defaults to lag the US.
The good news is that spreads are not tight and as we’ll see in the one-page default analysis summary overleaf, spreads adequately compensate buy-and-hold investors across the vast majority of historical default scenarios at a top-down level. This may not give mark-to-market investors any comfort when the next cycle hits but at least prices reflect some of the risks that are likely around the corner over the next two years.
Figure 1: Global Non-Financial BB
and B Annual Default Rates
0%
2%
4%
6%
8%
10%
12%
14%
16%
19
83
19
85
19
87
19
89
19
91
19
93
19
95
19
97
19
99
20
01
20
03
20
05
20
07
20
09
20
11
20
13
20
15
BB B
Source: Deutsche Bank, S&P
Figure 2: Non-Fin Debt to GDP vs.
US Single-B Default Rate
0%
2%
4%
6%
8%
10%
12%
14%
16%
35%
37%
39%
41%
43%
45%
47%
1985 1989 1993 1997 2001 2005 2009 2013
Non-Financial Debt to GDP (LHS)
US Single-B Default Rate (RHS)
Source: Deutsche Bank, Federal Reserve, S&P
Figure 3: European Bank Equity vs.
Non-Fin Lending
-10%
-5%
0%
5%
10%
15%
20%
0
100
200
300
400
500
600
2000 2003 2006 2009 2012 2015
Euro Stoxx Banks index (SX7E) [LHS]
Eurozone bank loans to non-fin. corporates (Advanced12m) [RHS]
Source: Deutsche Bank, ECB, Bloomberg Finance LP
Figure 4: US Defaults vs. Loan
Standards
0%
4%
8%
12%
16%
-50
0
50
100
1990 1994 1998 2002 2006 2010 2014
C&I Loan Standards (% net tightening, 4Q Lag, LHS)
US HY Default Rate (RHS) Source: Deutsche Bank, Bloomberg Finance LP, S&P
11 April 2016
Annual Default Study: Past the Point of No Return?
Page 4 Deutsche Bank AG/London
One-Page Default Analysis Summary
To compensate for defaults in the latest five-year cohort formed in 2011, investors would have required spreads of only 38bp in BBs and 133bp in Bs. This represents an increase from 23bp and 114bp, respectively, for the previous 2010 cohort which was effectively at historical lows. Current EUR/USD BB spreads are at 421/452bp and B spreads at 716/729bp.
Given average default rates in each rating category over time, moving down the rating spectrum leads to greater default spread premia for cash bonds unless we see a notably more aggressive default/recovery outcomes. However we should note here that with a zero DSP over five years, a HY investor’s performance would be on a par with safe government bonds, a hardly adequate outcome given the amount of risk taken. Therefore, higher DSPs as we move down the rating spectrum should be adjusted for greater variability in default outcomes.
In European and US CDS indices, which are tighter than their cash bond counterparts, DSPs are positive across recovery assumptions except for Crossover under recovery close to zero. Generally, given iTraxx Crossover is some 125bp tighter than CDX HY, the DSPs of the former are significantly lower than those of the latter. These measures, of course, are based purely on ratings and do not reflect the heightened investor fears of contagion in the US HY sector emanating from high and growing defaults in the metals & mining and oil & gas sectors in the US.
Additionally, we introduce a finer methodology to gauge whether current credit spreads for broad indices provide sufficient compensation for potential defaults. We calculate what spread on a current index would be necessary to compensate for the default experience of individual historical rating cohorts, given the distribution of ratings and maturities in the current index. We do so for baseline, stressed and super-stressed recovery levels and contrast them with current index spreads (Figure 9 to Figure 14), thus showing how default spread premia vary depending on what stage in the credit cycle we are currently in. At present, IG index spreads offer ample buffers against the worst historical default rates. In HY cash bonds, current spreads would largely compensate for even the worst default rates under baseline recovery assumptions. This is however not the case in Crossover/HY CDS indices that include similar ratings but trade at tighter spreads, implicitly pricing in a benign stage of the default cycle.
With over a decade of Crossover/CDX HY index default history, we provide the actual realised default rates and loss rates for each series (up to the maturity of the five-year tenor). The peak default (loss) rate for Crossover was 12% (10%) and it was 18% (14%) for CDX HY, which unsurprisingly occurred for series covering the worst of the financial crisis. Comparing these with rating-implied cumulative default rates (Crossover 16.2% and CDX HY 17.1%) and those implied by current spreads (Crossover 18.7-24.1% and CDX HY 25.7-32.8% for 20-40% recovery), historical defaults in CDS indices have been astonishingly low. Additionally, there has been a notable drop in the default rates since the peak of the financial crisis. The five-year Crossover series maturing in June 2016 has so far had a cumulative default (loss) rate of 2.5% (1.1%) and this has been 8% (5.7%) for CDX HY.
Figure 5: EUR cash DSP (bp)
0
100
200
300
400
500
600
700
AA A BBB BB B
Average Best Worst
Assumed 40% recovery. Source: Deutsche Bank, S&P
Figure 6: USD cash DSP (bp)
0
200
400
600
800
1,000
1,200
AA A BBB BB B CCC
Average Best Worst
Assumed 40% recovery. Source: Deutsche Bank, S&P
Figure 7: CDS index DSP (bp)
-50
0
50
100
150
200
250
Main
No
n-F
in
Fin
Sen
Fin
Su
b
Cro
ssover
IG HY
iTraxx CDX
0% Recovery
20% Recovery
40% Recovery
Source: Deutsche Bank, Mark-it Group
Figure 8: Crossover actual defaults
0%2%4%6%8%
10%12%14%
S1
(5
.2yrs
)S
2 (5
.5yrs
)S
3 (5
.2yrs
)S
4 (5
.2yrs
)S
5 (5
.3yrs
)S
6 (5
.2yrs
)S
7 (5.3
yrs
)S
8 (5.3
yrs
)S
9 (5
.3yrs
)S
10 (5.2
yrs
)S
11 (5.3
yrs
)S
12 (5.2
yrs
)S
13 (5.2
yrs
)S
14 (5.2
yrs
)S
15 (5.0
yrs
)S
16 (4.5
yrs
)S
17 (4.0
yrs
)S
18 (3.5
yrs
)S
19 (3.0
yrs
)S
20 (2.5
yrs
)S
21 (2.0
yrs
)S
22 (1.5
yrs
)S
23 (1.0
yrs
)S
24 (0.5
yrs
)S
25 (0.0
yrs
)
Default Rate
Source: Deutsche Bank
11 April 2016
Annual Default Study: Past the Point of No Return?
Deutsche Bank AG/London Page 5
Figure 9: iBoxx EUR non-fin. corp. IG
Figure 10: iBoxx USD non-fin. corp.
IG
Figure 11: iBoxx GBP non-fin. corp.
IG
0
100
200
1981
1982
1983
1984
1985
1986
1987
1988
1989
1990
1991
1992
1993
1994
1995
1996
1997
1998
1999
2000
2001
2002
2003
2004
2005
2006
2007
2008
2009
2010
2011
2012
Spre
ad to
co
ver
his
t. d
ef. r
ate
s (b
p)
Historical cohort
Assumed recovery: 60% sec., 40% sr. uns., 20% sub.Assume recovery: 40% sec., 20% sr. uns., 0% sub.Assumed recovery: 0% sec., 0% sr. uns., 0% sub.Bmk spread (6 Apr 2016)ASW spread (6 Apr 2016)
0
100
200
1981
1982
1983
1984
1985
1986
1987
1988
1989
1990
1991
1992
1993
1994
1995
1996
1997
1998
1999
2000
2001
2002
2003
2004
2005
2006
2007
2008
2009
2010
2011
2012
Spre
ad to
co
ver
his
t. d
ef. r
ate
s (b
p)
Historical cohort
Assumed recovery: 60% sec., 40% sr. uns., 20% sub.Assume recovery: 40% sec., 20% sr. uns., 0% sub.Assumed recovery: 0% sec., 0% sr. uns., 0% sub.Bmk spread (6 Apr 2016)ASW spread (6 Apr 2016)
0
100
200
1981
1982
1983
1984
1985
1986
1987
1988
1989
1990
1991
1992
1993
1994
1995
1996
1997
1998
1999
2000
2001
2002
2003
2004
2005
2006
2007
2008
2009
2010
2011
2012
Spre
ad
to
co
ver
his
t. d
ef.
ra
tes
(bp
)
Historical cohort
Assumed recovery: 60% sec., 40% sr. uns., 20% sub.Assume recovery: 40% sec., 20% sr. uns., 0% sub.Assumed recovery: 0% sec., 0% sr. uns., 0% sub.Bmk spread (6 Apr 2016)ASW spread (6 Apr 2016)
Source: Deutsche Bank, S&P Source: Deutsche Bank, S&P Source: Deutsche Bank, S&P
Figure 12: DBIQ EUR corp. HY Figure 13: DBIQ USD corp. HY Figure 14: DBIQ GBP corp. HY
0
200
400
600
800
1,000
1,200
1981
1982
1983
1984
1985
1986
1987
1988
1989
1990
1991
1992
1993
1994
1995
1996
1997
1998
1999
2000
2001
2002
2003
2004
2005
2006
2007
2008
2009
2010
2011
2012
Spre
ad
to
co
ver
his
t. d
ef.
ra
tes
(bp
)
Historical cohort
Assumed recovery: 60% sec., 40% sr. uns., 20% sub.Assume recovery: 40% sec., 20% sr. uns., 0% sub.Assumed recovery: 0% sec., 0% sr. uns., 0% sub.Bmk spread (6 Apr 2016)ASW spread (6 Apr 2016)
0
200
400
600
800
1,000
1,200
1981
1982
1983
1984
1985
1986
1987
1988
1989
1990
1991
1992
1993
1994
1995
1996
1997
1998
1999
2000
2001
2002
2003
2004
2005
2006
2007
2008
2009
2010
2011
2012
Spre
ad
to
co
ver
his
t. d
ef.
ra
tes
(bp
)
Historical cohort
Assumed recovery: 60% sec., 40% sr. uns., 20% sub.Assume recovery: 40% sec., 20% sr. uns., 0% sub.Assumed recovery: 0% sec., 0% sr. uns., 0% sub.Bmk spread (6 Apr 2016)ASW spread (6 Apr 2016)
0
200
400
600
800
1,000
1,200
1981
1982
1983
1984
1985
1986
1987
1988
1989
1990
1991
1992
1993
1994
1995
1996
1997
1998
1999
2000
2001
2002
2003
2004
2005
2006
2007
2008
2009
2010
2011
2012
Spre
ad
to
co
ver
his
t. d
ef.
ra
tes
(bp
)
Historical cohort
Assumed recovery: 60% sec., 40% sr. uns., 20% sub.Assume recovery: 40% sec., 20% sr. uns., 0% sub.Assumed recovery: 0% sec., 0% sr. uns., 0% sub.Bmk spread (6 Apr 2016)ASW spread (6 Apr 2016)
Source: Deutsche Bank, S&P Source: Deutsche Bank, S&P Source: Deutsche Bank, S&P
11 April 2016
Annual Default Study: Past the Point of No Return?
Page 6 Deutsche Bank AG/London
Past the Point of No Return?
There is clear evidence that the US credit cycle is more advanced than that seen in Europe even if the latter region is still trudging through what is very low nominal GDP growth. As we discussed in our 2016 Outlook, US credit fundamentals have deteriorated notably and the economy appears late cycle to us. As so much of the attention surrounding future defaults is currently focused on the US, especially given its exposure to the distressed Oil and Gas sector, in this main chapter of this year’s study we’ve attempted to advance the main discussion from last year’s study where we speculated that the next major default cycle is likely to be in full force in 2017-2018. To help us with this we’ve leaned heavily on work and discussions with our US credit strategists led by Oleg Melentyev.
Last year’s study focused on the yield curve as the main lead indicator for the default study but this year Oleg’s team has helped us broaden out some of the early warning indicators for the next default cycle. We’ve added European analysis where possible but the immaturity of the region’s HY market does not allow for a deep look back to previous cycles when attempting to highlight historical signals.
Stock and quality of HY debt
The buildup of excess is often a pre-requisite for bubbles to burst or for economic cycles to be vulnerable to shocks. One argument for why this US economic cycle might still be able to run for a few years is that many economists feel that excess hasn’t been as prevalent as in prior cycles. However one can argue there has been a sizeable increase in US corporate debt since the GFC comparable to increases prior to previous default cycles. As Figure 15 shows, in the modern era of leveraged finance the debt cycle waves have been well correlated to defaults. We’ve used single-Bs to keep credit quality constant throughout and used Fed data to determine non-financial corporate debt/GDP.
Figure 15: US Non-Financial Debt to GDP vs. US Single-B Default Rate
0%
2%
4%
6%
8%
10%
12%
14%
16%
35%
37%
39%
41%
43%
45%
47%
1985 1988 1991 1994 1997 2000 2003 2006 2009 2012 2015
Non-Financial Debt to GDP (LHS) US Single-B Default Rate (RHS)
Source: Deutsche Bank, Federal Reserve, S&P
Our US credit strategists measure the total growth of debt stock as well as its aggressiveness to determine whether there has been sufficient “material” created to feed the next wave of defaults. Figure 16 looks at the growth of the stock of US HY debt as well as the aggressiveness of new issuance. The former is measured by the combined size of the HY bond market (USD developed markets) and loans on U.S. bank balance sheets. The graph shows
11 April 2016
Annual Default Study: Past the Point of No Return?
Deutsche Bank AG/London Page 7
distinct periods of debt growth in the past, going back to the late 1980s, with each of the past three complete credit cycles preceded by waves of new debt creation, lasting from four to five and a half years, and resulting in cumulative debt stock growth of 53-68% (shaded areas). The current episode, measured since early 2011, has lasted 5.2 years and resulted in 64% growth in the combined value of the high yield bond market and loans on bank balance sheets, putting it comfortably inside the range of previous cycles. It shows a similar result to our own US corporate debt/GDP chart.
For a measure of aggressiveness in recent issuance trends, our US strategists look at CCC-rated issuance in HY and leveraged loans, as a percentage of total market size, as shown in the right-hand graph of Figure 16. Volume is presented as a percentage of total market size (HY + loans), on a trailing-12-month basis. Shaded areas again highlight previous debt growth cycles, as well as the most recent one, with figures printed inside representing cumulative CCC issuance volume for the full duration of each episode, divided by the market size at its start. The previous two credit cycles, in the late 1990s and mid- to late 2000s, saw this indicator expand by 20% and 18%, respectively, compared to its present value of 17%. Unfortunately, there is a lack of detailed issuance data to extend this to the first cycle in the late 1980s.
Figure 16: Prerequisites for the Next Default Cycle – Growth in Debt Stock (left) and Deteriorating Lending Standards
(right)
0.5
1.0
1.5
2.0
2.5
3.0
3.5
4.0
1986 1989 1992 1996 1999 2003 2006 2009 2013
Debt Growth Cycles
HY Market Size + Bank Loans, US$trln
4.5yrs, 55%
5.5yrs, 68% 4yrs, 53% 5.2yrs, 64%
0
1
2
3
4
5
6
1997 1999 2001 2003 2006 2008 2010 2012 2014
Debt Growth Cycles
Trailing 12m CCC Issuance % of HY Market Size
20% 18% 17%
Source: Deutsche Bank
The analysis is somewhat conservative in estimating the starting point of the current credit cycle to be January 2011. Arguably, the market was healing and perhaps even expanding in 2010, which would make these measurements of pre-requisite debt growth and aggressiveness look even more stretched here. We will nonetheless use the numbers shown above, as we aim to build our case for the timing of the next default cycle based on the more conservative assumptions.
It’s difficult to replicate the analysis for Europe as we don’t have the same depth of data. The only default cycle where the market had any critical mass was the one linked to the GFC. In the early-2000s the EUR HY market was small but heavily weighted to the eventually deeply distressed TMT sector. The left hand chart of Figure 17 shows EU-19 non-financial corporate debt to GDP based on data from the ECB. It’s fair to say that the lack of debt build-up since the financial crisis is a fair reflection of what has occurred in Europe and is in contrast to the debt accumulation seen in the US. In terms of lower quality issuance, Europe has obviously seen a pick-up in CCC issuance since the GFC but it’s been milder than in the US and nowhere near levels seen in the run up to the last default cycle.
11 April 2016
Annual Default Study: Past the Point of No Return?
Page 8 Deutsche Bank AG/London
Figure 17: Eurozone Non-Financial Debt to GDP (left) and CCC Issuance as a Percentage of the HY Market (right)
40%
45%
50%
55%
60%
65%
2000 2002 2004 2006 2008 2010 2012 2014
Non-Financial Debt to GDP
0%
1%
2%
3%
4%
5%
6%
2004 2005 2006 2008 2009 2011 2012 2013 2015
12m Trailing CCC Issuance as % of HY Market
Source: Deutsche Bank, ECB, Bloomberg Finance LP, Mark-it Group
So it’s fair to say that this analysis is one piece of evidence that the credit cycle is more developed in the US than in Europe. Obviously if the European economy fell sharply independently of the US it would render this analysis less useful but for now it feels like the US will lead the next default cycle.
We can therefore conclude that pre-requisites for the next default cycle are now in place. However as Oleg points out a stack of hay is not a fire hazard in and of itself; someone being careless with matches nearby makes it so. A strong enough volatility shock has played the role of trigger in each of the past three credit cycles where similar debt build up and issuance quality deterioration had previously occurred.
So what has previously helped trigger the subsequent default cycle and what indicators do we need to look out for. In their analysis our US strategists have previously tried to identify changes in potential lead indicators in the 12 months before the start of previous default cycles thus helping provide an early warning signal. They aggregated this work in their October 2nd 2015 piece “The Evolution of a Default Cycle”. We have borrowed some of their work below, added our own emphasis and tried to add a European angle where possible. However replicating the analysis in Europe is hamstrung by the fact that European HY has only experienced one full default cycle since it had any critical mass.
Figure 18 shows three graphs depicting HY issuer default counts at around the time each of the past default waves emerged – in the early 1990s, late 1990s, and late 2000s. The graphs highlight 12 months prior to the arrival of each default wave with shaded areas, and determine their ending points to be in July 1989, August 1998, and October 2007, respectively. So by design, these 12-month stretches are chosen as periods leading to subsequent defaults. The aim is then to find indicators that have shown a clear and consistent propensity to generate an identifiable signal within those last 12 months leading to each of the past three credit cycles. Indicators that sent false positives – those that repeated their signals in the absence of a subsequent jump in defaults – were discarded.
11 April 2016
Annual Default Study: Past the Point of No Return?
Deutsche Bank AG/London Page 9
Figure 18: How it all Started in the Past – Last 3 Credit Cycles, Zoomed in Views of Lift-Off in Defaults
0
2
4
6
8
10
12
Jan 88 Jul 88 Jan 89 Jul 89 Jan 90 Jul 90
12mo Prior to Cycle Default Count
0
5
10
15
20
Jul 97 Jan 98 Jul 98 Jan 99 Jul 99 Jan 00
12mo Prior to Cycle Default Count
-2
3
8
13
18
Apr 06 Oct 06 Apr 07 Oct 07 Apr 08 Oct 08
12mo Prior to Cycle Default Count
Source: Deutsche Bank
As discussed above, debt build-up alone doesn’t in itself guarantee an imminent default cycle. It is likely an important pre-requisite but needs further catalysts. A big potential trigger identified by our US strategists is a volatility shock which is best and most easily measured in terms of equity volatility.
Figure 19 shows the VIX equity volatility index, with highlights in lighter blue representing the pre-cycle 12-month periods, as defined by the shaded areas in Figure 18. A reading of 30pts on the VIX scale has been reached consistently at the beginning of each of the last three credit cycles. In this cycle it has briefly spiked above this in August 2015 (for 3 days peaking at 40.74 on 24 Aug 2015 and over 50 intra-day) for the first time since 2011, remaining above 20 until early October. We then saw another burst of volatility in early 2016 with the VIX range trading between 20-30 for 7 weeks (peaking at 28.14 – 11 Feb 2016) before settling back down towards the lows.
Figure 19: VIX Index – A Pre-Default Cycle Trigger?
10
15
20
25
30
35
40
1988 1991 1994 1997 2000 2003 2006 2009 2012 2015
VIX Pre-cycle 12mo
Source: Deutsche Bank, Bloomberg Finance LP
The focus has been on the VIX spikes highlighted in lighter blue and readers can easily spot that that the analysis hasn’t identified other spikes. This is mainly because we are interested in later cycle default wave triggers here, i.e. events that occur before the waves get started, as opposed to those that are coincident with their ongoing evolution. Almost all of the subsequent shocks happened when the default cycle was already under way, such as mid-to late 1990, 2000-2002, and 2008-2009. One notable exception was September 2011, following the US downgrade and debt ceiling debacle, when VIX exceeded 40pts at a time when the previous default cycle was already behind us. Why the exception? We believe that three factors must be present at the same time. In that case, while the volatility shock was certainly there, two other crucial elements were arguably absent as the debt growth cycle was in its early stages and monetary policy was still ultra-easy and the yield curve still very
11 April 2016
Annual Default Study: Past the Point of No Return?
Page 10 Deutsche Bank AG/London
steep. So this was still early cycle with the investment climate attractive enough to offset the volatility spike.
As discussed above this analysis suggests we need the combination of three conditions for us to be confident the next default cycle is around the corner. We need the accumulation of excessive debt and preferably of deteriorating quality, some kind of external shock/trigger and a sharp flattening of the yield curve.
Yield curve – A reliable indicator of future defaults
In last year’s Default Study we showed the link between the yield curve and lending standards and then onto defaults. Both parts of this chain operate with a lag. Figure 20 shows the relationship between the US yield curve (10-year UST minus the Fed Funds rate) and lending standards (left) and lending standards and defaults (right). The lag is 6 and 4 quarters respectively. This means that the yield curve leads defaults by 10 quarters.
Figure 20: US C&I Loan Standards vs. US Yield Curve (Advanced 6Q, left) and vs. US HY Default Rate (Lagged 4Q,
right)
-100
0
100
200
300
400-40
-20
0
20
40
60
80
100
1990 1993 1996 1999 2002 2005 2008 2011 2014 2017
C&I Loan Standards (% net tightening, LHS)
FFs10s Curve (6Q Lag, Inv, RHS)
0%
4%
8%
12%
16%
-40
-20
0
20
40
60
80
100
1990 1993 1996 1999 2002 2005 2008 2011 2014
C&I Loan Standards (% net tightening, 4Q Lag, LHS)
US HY Default Rate (RHS)
Source: Deutsche Bank, Bloomberg Finance LP, S&P
As we have previously highlighted we have now seen two consecutive quarters of net tightening of lending standards in the US and previously whenever this has happened it has ultimately led to a full blown default cycle – albeit with only three cycles of data to examine. The current level of net tightening (+8) is consistent with a US default rate above 4.5% by the end of the year relative to 3.4% now and a long-term average of 4.3%. Looking at the US yield curve in isolation, the years leading up to the initiation of each of the past four recessions saw steady but significant curve flattening and interestingly all contained a period where a mild inversion occurred shortly before the recession hit (Figure 21, left). The right hand chart of Figure 21 shows the relationship back nearly 80 years and again virtually all recessions were preceded by a flattening curve without necessarily requiring an inversion.
11 April 2016
Annual Default Study: Past the Point of No Return?
Deutsche Bank AG/London Page 11
Figure 21: US 2s10s Curve vs. Recessions – since 1977 (left) and since 1941 (right)
-300
-200
-100
0
100
200
300
1977 1982 1987 1992 1997 2002 2007 2012
2s10s
-300
-200
-100
0
100
200
300
1941 1949 1957 1966 1974 1983 1991 1999 2008
2s10s
Source: Deutsche Bank, Bloomberg Finance LP, GFD, NBER
The good news today is that the US curve is still reasonably positive, the bad news is that it’s well off the steepest point back in February 2011. We have seen around another 35bps of flattening since last year’s study – weighted more towards a rise in yields at the front end of the curve. All points to a tightening of lending standards without yet signaling the end of the cycle.
Throughout this analysis there is no definitive smoking gun evidence that the next default cycle is round the corner but we’re building a theme that a combination of factors are pulling together to increase the risks of the cycle turning. Indeed looking at the yield curve perhaps helps one understand why the sell-off with the VIX at 40 in late 2011, and perhaps the stresses of the European crisis in 2012, did not lead to a default cycle. The yield curve (and central bank policy) was just way too steep (easy) for negativity to develop as investors had the very positive carry of a steep yield curve as a large cushion as the storm passed. We also had not seen the cumulative build-up in debt that we now see today.
Obviously with the Fed easing off from their planned series of rate hikes so far in 2016, the flattening pressures are less acute than they could have been. Nevertheless with aggressive QE elsewhere (Europe and Japan) and with the weakness in the global economy, the long-end of the curve seems to repeatedly have a gravitational pull lower in yield whenever we see any back-up. Thus steady flattening is occurring in the US even without the Fed being as aggressive as the market thought they would be at the back end of 2015. Globally all major developed market 10yr vs. 2yr yield curves – US, Eurozone, Japan, UK, Canada, Australia, Korea, and Singapore – are flatter today than at the beginning of 2016. Figure 22-Figure 25 helps show this for Germany, UK, Japan and the Eurozone (the latter on a GDP-weighted basis).
11 April 2016
Annual Default Study: Past the Point of No Return?
Page 12 Deutsche Bank AG/London
Figure 22: Germany 2s10s Curve (bps) Figure 23: Eurozone (GDP Weighted) 2s10s Curve (bps)
-250
-200
-150
-100
-50
0
50
100
150
200
250
300
1967 1972 1978 1983 1989 1994 2000 2005 2011
Germany
0
50
100
150
200
250
300
2004 2005 2006 2008 2009 2011 2012 2013 2015
Eurozone
Source: Deutsche Bank, Bloomberg Finance LP, GFD Source: Deutsche Bank, Bloomberg Finance LP
Figure 24: UK 2s10s Curve (bps) Figure 25: Japan (2s10s Curve (bps)
-200
-150
-100
-50
0
50
100
150
200
250
300
350
1979 1983 1987 1991 1995 1999 2004 2008 2012
UK
-150
-100
-50
0
50
100
150
200
250
300
1980 1984 1988 1992 1996 2000 2004 2008 2012
Japan
Source: Deutsche Bank, Bloomberg Finance LP, GFD Source: Deutsche Bank, Bloomberg Finance LP, GFD
There is a school of thought that the yield curve is a less reliable lead indicator this cycle due to the distorted nature of both the front and back end of government yield curves due to near zero and negative short-term rates and QE at the long-end. This could work both ways as perhaps financial repression is preventing what would now be a flat or inverted curve in many parts of the world and therefore we risk missing the free market signal until it’s too late. The alternative view would be that central banks are controlling the market so much, keeping yields so low that investors are likely to continue to invest in credit for longer in a search for lost yield and thus the yield curve is less relevant today. We’re not sure whether the yield curve is any more or less relevant than it was in the past but what we like about it as an indicator is what it says about animal spirits and risk appetite. A steep yield curve forces investors further down the risk spectrum and further out the term structure. A flat or inverted yield curve ensures that the opportunity costs are low for those shunning term and credit risk along the curve. So the yield curve is fundamental to the economic and default cycle, in our opinion.
The situation in Europe is confusing as Figure 22 and Figure 23 show that the German and GDP weighted European curve have both been flattening even with negative rates leading to a front-end rally. The long-end continues to perform and one of the problems with QE in Europe is that it is putting continual flattening pressure on the yield curve. However the ECB actions are also continuing to keep fixed income markets well bid and this must ensure that many investors scramble into credit to maintain yield. The fact that European credit spreads have widened since QE started a year ago (a period
11 April 2016
Annual Default Study: Past the Point of No Return?
Deutsche Bank AG/London Page 13
where the yield curve has flattened) perhaps argues that the scramble for yield is a better theory than reality though. Further complicating matters is the ECB’s recent decision to purchase IG Eurozone non-financial corporate bonds. If they prove successful in buying size (a big ‘if’) then this should improve the ability of corporates to refinance. Although aimed at IG, HY should still benefit from better relative value once purchases start. As we said though the jury is still out on how successful they’ll be.
So far a flatter yield curve hasn’t impacted European lending standards. We have continued to see net loosening which should be supportive for a path of continued low default rates in the near future.
Figure 26: European HY Default Rate vs. European Lending Standards
(Advanced 4Q)
0%
2%
4%
6%
8%
10%
12%
-20
-10
0
10
20
30
40
50
60
70
80
2003 2005 2007 2009 2011 2013 2015
Lending to Enterprises (% net tightening, 4Q Lag, LHS) Europe HY Default Rate (RHS)
Peaks above 20%
Source: Deutsche Bank, Bloomberg Finance LP, S&P
However some caution is required in Europe. As we’ll see in the next sections the recent slump in European bank equities could have major ramifications for the future path of lending standards and hence defaults. So there is slightly conflicting evidence here and one could argue that the ECB’s aggressive actions are actually impeding banks’ ability to make a profit which in turn may impact future lending standards.
Financial sector equities – a worrying lead indicator? To reiterate, we have found that three factors lead to a turning point in defaults: aggressive debt growth, a volatility shock, and tight monetary policy. We discussed all three above but one additional variable that perhaps straddles volatility and transmission of monetary policy is the financial sector. We focus in particular on their equity performance as this may provide the greatest insight into the sector’s ability, willingness or confidence to open or close the lending spigots and is thus a potentially good early warning indicator of tighter credit conditions.
Our US strategists have pointed out that US Financial equities have tended to underperform the S&P500 by 15-20% in the year leading up to the previous three default cycles we’ve identified. As we stand today they are underperforming the index by around 10% since reaching their recent peak level in Aug 2015. Within Financials, US banks are underperforming SPX by 19%. Importantly, both of these metrics are at the lows of their recent ranges, refusing to show any improvement alongside of a market rally that has taken place since early February 2016.
11 April 2016
Annual Default Study: Past the Point of No Return?
Page 14 Deutsche Bank AG/London
Figure 27: US Financial Sector Equity Performance Ahead of Default Cycles
80
85
90
95
100
105
1988 1991 1994 1997 2000 2003 2006 2009 2012 2015
Financial Equities / S&P500 Ratio (Normalized) Pre-cycle 12mo
Source: Deutsche Bank, Bloomberg Finance LP
In Europe the signal is even more negative. Of particular concern is the relationship shown in Figure 28 where we show the Euro Stoxx bank equity index versus bank loans to non-financial corporates advanced 12 months. The correlation is strong and hints at a potential reduction in actual loans over the next 12 months which could obviously have major ramifications for the default rate. This is particularly worrying given that the we’re only a month on from an ECB meeting where the council provided a spectacularly accommodative package that was geared to be helpful to banks with the hope that banks would in turn be willing to lend to the wider economy. So although bank equity is highly volatile the indicators currently look worrying in the US and perhaps more so in Europe.
Figure 28: Euro Stoxx Banks Index vs. YoY Change in Lending to Non-
Financial Corporates (Advanced 12m)
-10%
-5%
0%
5%
10%
15%
20%
0
100
200
300
400
500
600
2000 2002 2004 2006 2008 2010 2012 2014 2016
Euro Stoxx Banks index (SX7E) [LHS]
Eurozone bank loans to non-fin. corporates (Advanced12m) [RHS]
Source: Deutsche Bank, Bloomberg Finance LP, ECB
Conclusion The discussion above adds weight to our long standing view that 2017-2018 could mark the next fully established default cycle. The variable that perhaps is still offering some hope that a full cycle can be delayed is that the US yield curve hasn’t yet flattened enough to provide a strong signal even if it does suggest a continuing tightening of lending standards and rising defaults. The fact that many other major country yield curves continue to flatten and in many cases are getting close to flat offsets some of the comfort from the US.
Also complicating the matter is this era of heavy financial repression and very active central banks. Are we still in a period where default rates are likely to remain artificially suppressed even if we do see a full cycle? Figure 29 shows that even though 2015 showed signs of defaults picking up, single-B and BB
11 April 2016
Annual Default Study: Past the Point of No Return?
Deutsche Bank AG/London Page 15
default rates were still comfortably below their long-term average which they have been for 11 of the last 12 years with 2009 the only exception. Indeed last year’s default rate for single-Bs (up from 0.9% to 2.7%) was still lower than all of the first two decades of the modern era of leveraged finance up to 2003. So in spite of all the challenges we face (too much debt and very low growth being the highlights), this era has been characterized by astonishingly low default rates.
Figure 29: Global Non-Financial BB and Single-B Annual Default Rates
0%
2%
4%
6%
8%
10%
12%
14%
16%
19
83
19
84
19
85
19
86
19
87
19
88
19
89
19
90
19
91
19
92
19
93
19
94
19
95
19
96
19
97
19
98
19
99
20
00
20
01
20
02
20
03
20
04
20
05
20
06
20
07
20
08
20
09
20
10
20
11
20
12
20
13
20
14
20
15
BB B
Source: Deutsche Bank, S&P
The artificial ingredients keeping defaults below their 1983-2003 levels are still broadly in place so although we expect the next default cycle to be round the corner it could still be mild relative to the early 90s and early 00s cycle and even the already subdued 2009 cycle which was very short, especially given the economic wreckage seen.
As we’ve suggested in previous editions of this report, this is likely due to the increasing artificial demand for fixed income seen over the last 15-20 years which effectively allows more financing opportunities for levered companies at lower yields than they might be asked to pay if global fixed income markets were a perfectly free market where the only consideration was relative value. Over the last two decades, SWFs, pension funds, insurance companies, banks and more recently central banks in great size have distorted the demand for and yield of global fixed income. This is unlikely to change and although the Oil and Gas sector demonstrates that bad fundamentals can still win out, for more marginal companies, the artificial conditions in fixed income could still help prevent a more savage cycle.
Obviously the Oil and Gas sector will play a big part in determining the overall level of defaults and in a separate section our US strategists detail their expectations for defaults in this sector and how that will filter through into the wider US HY market.
It’s also true that credit spreads are relatively elevated and price in a default rate markedly higher than current levels. Indeed as we’ll see throughout the body of this report, at an aggregate level a buy-and-hold investor would need to see defaults worse than virtually all observed periods through history for them not to get a positive excess return relative to Government bonds from this starting point. However if we do see a recession even if defaults are relatively subdued the illiquidity of financial markets could easily see big mark-to-market losses. Recession tend to bring big overshoots in credit spreads relative to default risk anyway. So lower structural defaults may not provide comfort in the heat of the next recession but current spreads should give longer-term investors some comfort across the vast majority of sectors. The next section does argue though that US Oil and Gas may not fully price in default risk so credit work is still essential in any HY portfolio.
11 April 2016
Annual Default Study: Past the Point of No Return?
Page 16 Deutsche Bank AG/London
US HY Default Rate Outlook
This section has been contributed by our US credit strategists, Oleg Melentyev and Daniel Sorid
US HY appears to be in a more advanced stage in its credit cycle, compared to European trends discussed so far. Primarily this comes as a function of its relatively significant weight in commodity sectors, which we estimate to be over 20% in principal value terms. This segment of the market is already defaulting at a 20% rate over the past 12 months, as the graph on the right demonstrates, and we expect defaults to stay at these elevated levels for foreseeable future.
Most of these energy defaults have so far taken the form of distressed exchanges with an average recovery around 28 cents on the dollar; going forward we would expect to see more actual bankruptcies with the likely consequence of further pressures on recoveries here.
The ex-commodity default rate, shown as a lighter blue line on this graph, has remained stable and low so far, at around 2%, and we expect this line to begin trending higher as this year progresses. We currently expect to see this line reaching 4% in a year from now, which still represents only a modest increase compared to full cyclical peak levels of around 12-15% (depending on which agency you use). At the same time, this would be the highest level this rate has experienced post-GFC, if materialized.
Certain factors we believe to have leading relationships to US defaults are behind this view, including volatility shocks and highest-quality corporate spreads, which have previously breached levels consistent with a turning credit cycle (30pts on VIX scale, and 100bp on AA OAS). Two other indicators we are watching closely here are bank stocks and Treasury yield curve. The former has recently shown a 15%+ underperformance in the bank equity index relative to S&P500, close to its lows so far YTD. Previously, we have noted that an underperformance of more than 20% happened prior to cyclical turns in defaults.
The USD yield curve has a relatively steep 2s10s slope of 100bps, which would normally be considered a safe distance away from being completely flat, as it has been prior to cyclical turns in the past. We wonder, however, to what extent the heavy-handed central bank presence on both ends of this curve today distorts this picture, an important development we discussed in greater detail here. We continue to watch these two indicators closely given their levels and recent performance trends (both failed to participate in the most recent rebound since early Feb). A material move in either one of them would likely have meaningful consequences for credit pressures in the US going forward.
US HY energy: applying the telecom template from 2001-2002 Given the extent of recent losses in the energy space, many investors are asking a question to what extent valuations there are currently reflecting some sort of the worst-case experience of other sectors. To help us opine on such a scenario, we look back at the deepest industry credit loss experience to-date: telecoms in 2001-2002. Figure 31 and Figure 32 below are demonstrating trailing 12-months par-weighted default rate in DM HY telecoms (left) and their average senior unsecured recoveries (right).
Figure 30: DM USD HY default rates
0
5
10
15
20
2001 2003 2005 2007 2009 2011 2013 2015
DM HY, All Sectors
DM ex-Commodities
DM Commodities
Source: Deutsche Bank
11 April 2016
Annual Default Study: Past the Point of No Return?
Deutsche Bank AG/London Page 17
A couple of initial observations from this data: this sector experienced most of its credit losses in the first two years, with 2001 contributing a 20% default rate, followed by a 32% default rate peak in 2002. Combined, these two years resulted in a 45% cumulative default rate ($100 * .8 * .68 = $55). Recovery rates oscillated around 30% for most of the time, bottoming out at 20% in late 2002, although there were several months with zero recoveries (Figure 30 shows trailing 12mo averages, masking those).
Figure 31: HY telecom default rates in early 2000s Figure 32: HY telecom recovery rates in early 2000s
0
5
10
15
20
25
30
35
40
2001 2002 2003 2004 2005
DM HY Telecom Default Rate
15
25
35
45
55
65
75
85
2001 2002 2003 2004 2005
DM HY Telecom Recovery Rate
Source: Deutsche Bank Source: Deutsche Bank
In Figure 33 we show a valuation framework familiar to our readers from past publications, which is updated here to reflect current dollar prices of energy bonds, as well as cumulative defaults and recoveries from the telecom experience described above.
11 April 2016
Annual Default Study: Past the Point of No Return?
Page 18 Deutsche Bank AG/London
Figure 33: Applying telecom 2001-2002 template to energy bonds today
Yr 1 Yr 2 T0 Yr 1 Yr 2
Price Coupon Cpn Yield Recovery
BBB 3 7 94.9 5.5 5.8 30.0 BBB 100 98 95
BB 6 15 88.0 6.0 6.8 25.0 BB 100 96 89
B 18 42 75.4 7.4 9.8 20.0 B 100 87 69
CCC 65 90 41.3 8.4 20.3 15.0 CCC 100 59 43
All HY Energy 26 45 71.3 7.1 11.4 20.5 All HY Energy 100 82 68
BBB 5.4 5.3
BB 5.8 5.5
B 6.9 5.7
CCC 6.7 4.3
All HY Energy 6.5 5.4
BBB 30.0 15.0
BB 25.0 12.5
B 25.0 15.0 7.5
CCC -- --
BBB 95 91 82
BB 88 81 70
B 75 62 52
CCC 41 41 41
All HY Energy 77 69 60
IRR
BBB 95 94 83 -4
BB 88 84 68 -9
B 75 60 42 -21
CCC 41 31 22 -19
All HY Energy 77 68 52 -13
Mkt Value (Credit Loss + Coupon + Downgrades)
Cumulative Deault Rate Surviving Par
Coupon
Percent Downgraded
Dollar Prices, Adjusted for Downgrades
Source: Deutsche Bank
In arriving at cumulative default rates by rating category, shown in the top-left corner, we goal-seek them to fit their betas to each other as well as 20/45% overall totals outlined a moment ago. We also applied weights to each rating category reflecting the current composition of the DM USD energy sector. Note how this scenario assumes a 90% cumulative default rate in energy CCCs and 42% in single-Bs. For recovery rates, we are using a sliding scale of 30% in BBBs down to 10% in CCCs, with a blended average close to 20%.
The right-hand side part of this table represents cash-flow analysis and IRR calculations based on these assumptions. Using single-Bs as an example here, a $100 portfolio invested in an average credit today, will experience 42% cumulative default rate in the next two years and will come out with $69 of remaining value, given that its distance to the default value is only $55 (current price $75 and recovery assumption $20). The weights for the overall HY energy are 35%, 40% and 25% for BB, single-B and CCC respectively.
The value of $69 represents the $58 of par bonds that did not default plus the recovery rate of $11 on defaulted bonds (e.g., (42% default * $ 20% recovery) / $75 purchase). This portfolio also collects $6.9 and $5.7 in coupons in years one and two, calculated at coupon rate over par.
It also experiences 15% downgrades to CCCs in year one, and 7.5% in year two, with downgraded names marked at CCC prices. These assumed downgrade rates are consistent with cyclical peak experiences in the past. Finally, the Market Value segment in the bottom right-hand corner combines all these steps, and calculates IRRs for each rating segment.
11 April 2016
Annual Default Study: Past the Point of No Return?
Deutsche Bank AG/London Page 19
All categories are showing negative expected IRRs from here given a recent run-up in prices. In a report published in early February we have pointed out how CCCs were poised to show positive IRRs from their lows around 28 cents back then. Today, following a nearly 40% run-up in prices, this is no longer the case. The CCC segment is also the most sensitive to a recovery assumption, in that a $10 assumption instead of $15 results in another 10% hit to IRR.
Higher-quality segments are also showing negative expected IRRs, and are not particularly sensitive to reasonable changes in recovery assumptions. For instance, single-Bs are still showing negative IRR at 30% recovery and BBs at 35%. Assumptions of higher recoveries in energy seem unrealistic.
Figure 34 and Figure 35 take a different angle at this question but arrive at a similar conclusion. On the left, we are showing where energy CCC names are trading today and contrast them to CCC price experiences in the past cycles in telecoms, autos, and gaming. At their lows close to $25, energy CCC bonds were trading very close to levels where similarly-rated names in the most affected sectors bottomed out in the past. At $41 today, they are just close to historical ranges for sectors in the midst of restructuring, providing little in a way of particular interest here.
Figure 34: CCC prices in energy, telecoms, autos, and
gaming
Figure 35: Overall HY prices in these sectors
20
40
60
80
100
2000 2003 2006 2009 2012 2015
Do
llar
Pri
ce, p
ts
CCCs Telecom CCCs Auto CCCs
Gaming CCCs Energy CCCs
40
50
60
70
80
90
100
110
2000 2003 2006 2009 2012 2015
Do
llar
Pri
ce, p
ts
USD DM HY Telecoms Autos
Gaming Energy
Source: Deutsche Bank Source: Deutsche Bank
Contrast this to what is shown on the right-hand graph, where similar sector relationships are plotted for broad HY, unconstrained by ratings. At $71 average price, overall energy HY is still trading at least $20 points away from what each of those three sectors achieved consistently ($50), and arguably even more, if stressed-tested against autos experience in 2008-2009 ($41).
This additional evidence reinforces conclusions we have drawn earlier in that expected IRRs in some form of a worst-case industry scenario is no longer priced in here. With revenues on track to take a 70% hit once the remaining hedges roll off, we think such a stress test is appropriate.
11 April 2016
Annual Default Study: Past the Point of No Return?
Page 20 Deutsche Bank AG/London
US and European Default Rate Scenarios for 2017-2018
In terms of thinking about what levels of annual HY default rates are possible in 2017 and 2018 let’s start with the US. Normal cyclical peaks are somewhere between 12-15% (depending on the cycle and which rating agency one uses), and invariably there is a sector or two that contribute disproportionately. It was telecoms in 2001-02, consumer discretionary in 2008-09, most likely commodities/EM related sectors in this upcoming cycle. Given all the artificial stimulus, outside of the commodities/EM, defaults should come in below previous market peaks. Whether it's 6-8% or a touch higher, say 8-10% would depend on where global growth is and how effective central banks are going to be in managing a contraction with zero rates as a starting point. It might also depend on whether governments can pick up the much needed stimulus baton from central banks and thus help growth and where low/negative rates and QE prove to be a good pain killer. With commodity related sectors included this number should be in the 9-11% range under the milder scenario but perhaps closer to 12-15% under the more stressed scenarios. For now the milder scenario is our central case.
Another argument suggesting why credit losses should not be materially higher in this cycle than in the past is that growth expectations are low to begin with. Most asset mispricings, and thus excess corporate leverage, are created when people get too optimistic about growth prospects, and that usually comes on the back of strong recent performance. One can argue this is what happened with commodities and EM. Growth expectations in these areas were high post-GFC and they therefore attracted much fresh capital and investment.
Too much optimism in growth prospects is probably not the greatest issue for other sectors in this current cycle. From this perspective alone, it’s reasonable to expect ex-commodity defaults on the lower side of historical experience if we see a full cycle, so if other factors cooperate, 6-8% could be realistic in the US. However policy errors or a worst recession could easily lift this up into the 8-10% range (12-15% with commodities). A lot can change between now and the end of 2017 and 2018 but assuming we’re right that the next full default cycle is creeping up, these are our current thoughts.
For Europe it’s hard when you look at the composition of the market to see how defaults will approach these levels over the next 2-3 years. The ECB’s heavy involvement in fixed income markets could also ensure a more sanguine default environment. However if we’re correct about being late cycle with a global recession a strong possibility in 2017 or 2018, then defaults will come. At this stage it’s hard to be too quantitative about levels in Europe but our expectations would be an annual HY rate peaking out between 5-7% in these years under our milder central scenario. In 2016 we could still see European defaults below 3% so there is still no immediate risk of a sharp increase.
Overall the numbers above for both the US and Europe would ensure the next cycle is still inside previous peaks (comfortably so in Europe). Given that the later sections of this report suggest that spreads generally compensate for virtually all historical default observations (vs. Govt. benchmarks) then these numbers can still provide comfort to a buy-and-hold investor. However we’d stress that recessions and default cycles always bring overshoots and a higher risk premium embedded into credit spreads. So comfort for the buy-and-hold investor, less so for those mark-to-market investors when the next cycle reaches its peak.
11 April 2016
Annual Default Study: Past the Point of No Return?
Deutsche Bank AG/London Page 21
Long-Term US Default Model
In this section we update our long-term default model, which was the focus of last year’s default study (“2017-2018 – The Next Default Cycle?”, 15 April 2015). For the US, the model contained two variables, the slope of the curve (10yr Treasury Yield – Fed Funds Target Rate) and the 10 year real Treasury yield (10yr Treasury Yield – US YoY CPI). Please see last year’s note for a more detailed rationale for using these variables. In Figure 36 and Figure 37 we show the time series for both of these variables. The dotted line highlights the change since we published last year.
We have already discussed the shape of the curve at length in the opening chapter but as an addition it’s worth pointing out that since the GFC the slope of the curve has been this flat on two previous occasions (Jul 2012, Jan 2015) so we could argue that the moves in the slope of the curve have not yet taken us to particularly unprecedented post-GFC levels. However the trend of flattening has global momentum.
Figure 36: US 10yr-Fed Funds Curve (bps) Figure 37: US Real 10yr Yield (%)
-200
-100
0
100
200
300
400
500
1985 1989 1993 1997 2001 2005 2009 2013
FFs10s Curve (bps)
-4
-2
0
2
4
6
8
10
1985 1989 1993 1997 2001 2005 2009 2013
Real 10yr Yield (%)
Source: Deutsche Bank, Bloomberg Finance LP Source: Deutsche Bank, Bloomberg Finance LP
In Figure 38 we show the update of the model. Looking towards the end of 2017 and into 2018, the model suggests the US HY default rate should be up around the 4% level and not far off our US strategists’ 12 month ex-Energy forecast. One of the weaknesses of the model is that although it predicts turning points fairly well, it historically signals default rates peaking out in the 6-8% range. Such a macro model struggles with sectors (like TMT in the early 2000s and Energy today) where fundamentals overwhelm the macro. So the reasons behind our US strategists’ 12 month default forecast of over 7% (including Energy) will never be captured by such a model.
The other problem with the model is that when a default cycle hits, often defaults feed on themselves as fear spreads through markets and funding dries up in a credit crisis. So whereas the model peaks out consistently at 6-8% historically, we’ve actually tended to peak out in the 10-12% range in reality (using S&P data – Moodys’ data has peaked at a higher rate).
11 April 2016
Annual Default Study: Past the Point of No Return?
Page 22 Deutsche Bank AG/London
Figure 38: US HY Default Model vs. Actual Default Rate
0%
2%
4%
6%
8%
10%
12%
14%
1988 1992 1996 2000 2004 2008 2012 2016
Default Rate Model Default RateR2 = 49%
Source: Deutsche Bank, S&P
To get the model to point to defaults in the 6-8% range consistent with previous default cycle peaks, we would most likely need to see the US YC flatten closer to zero. Real yields are less likely to change materially in a world of strong financial repression. Although global yield curves are generally much flatter than in the US, the current level of the US curve still provides some hope that the default rate can be more contained than in previous cycles. There is still time for this to deteriorate though as discussed elsewhere with central banks artificially suppressing rates, it could be that curves don’t need to become completely flat in this cycle to see the same default trigger as in previous cycles. So this is a caveat to the model and why we’ve tried to add other triggers in the main section of this report.
The rest of this study focuses more on current spread levels and assessing whether they would compensate for various historical default outcomes.
11 April 2016
Annual Default Study: Past the Point of No Return?
Deutsche Bank AG/London Page 23
Historical Default Analysis
A key theme of this report in recent years has been the extraordinarily low default environment we have been in for over a decade now. As we discuss elsewhere in this note there is a possibility that this could be coming to an end especially in the US. How severe the next default cycle will be is still open to question though.
Having spent time so far assessing the likely outlook for defaults, in this broad section we take a more mechanical look at defaults whereby we compare current spreads with actual realised historical default outcomes. We look at longer-term averages as well as actual default cycles by cohort. Ultimately the assessment we make here is whether credit spreads are likely to compensate for historical default risk and is very much viewed from a buy-and-hold perspective relative to the underlying government benchmark.
The results generally show that at these wider current spreads, credit compensates for virtually all historical scenarios. This will give the buy-and-hold investor some comfort as they read the rest of this report. However we accept that if we are about to head into a full blown default cycle then the mark-to-market risk will likely be significant as markets always overshoot and always require a risk premium above the bare minimum default protection. So there is no doubt that heavy mark-to-market losses would still be possible under the scenarios painted earlier in this report.
Cohort analysis
In this sub-section we try to provide a framework for thinking about what’s priced in by comparing current spreads to spreads that would have been required to compensate for default based on all realised 5-year cohorts over the last 30+ years using different recovery assumptions. This has been a regular feature of this report but has previously been based solely on global default rates, this time we have also looked at the specific European cohorts seen through time.
We also then provide an additional analysis where we calculate default-compensation spreads for benchmark cash and CDS indices. This is our new visual tool for assessing the adequacy of spreads on current indices given their rating and maturity composition and the past default experience of each rating category in individual historical cohorts. This allows us to assess how current spreads compare to spreads that would have been required by buy-and-hold investors on the current index to compensate for actual historical default paths starting at various points in the past. This methodology shows the variation of default-compensation spreads over the past credit cycles and indicates what the current default spread premium might be depending on which stage of the credit cycle we are in.
We should note here that having previously used Moody’s data for this analysis we have now switched to using S&P data, which has limited impact on the general outcome of the analysis.
Cohorts vs. current spreads
Global cohorts We start by looking at defaults globally with the analysis based only on non-financial issuers. We calculate spreads required to compensate for default
11 April 2016
Annual Default Study: Past the Point of No Return?
Page 24 Deutsche Bank AG/London
based on each actual 5-year discreet cohort formed since 1981 (based on S&P data). We have tried to calculate the compensation spreads taking into account the path of defaults over the 5-year horizon. Overall, this analysis is useful for showing where current spreads are across the board and in which periods through history these spreads would have (and wouldn’t have) compensated for the risk of default and by how much. We use both 40% and 0% recoveries as exact recoveries by cohort are not available. This provides us with a compensation range.
Figure 39: Non-Financial Spreads (vs. Governments) by Rating (bps)
Currency IG AA A BBB HY BB B CCC
Current EUR 126 75 98 156 534 421 716 2,080
USD 169 91 123 226 710 452 729 1,553
GBP 176 101 145 211
Wide since 2007 EUR 389 197 330 545 1,925 1,399 2,460 6,160
USD 541 303 468 672 1,857 1,234 1,825 2,992
GBP 392 202 332 570
Tight since 2007 EUR 49 25 42 59 217 154 261 475
USD 93 55 76 108 212 142 260 475
GBP 84 63 82 95
Source: Deutsche Bank, Mark-it Group
In Figure 40 we show the results of our analysis across IG and HY for each rating band (AA, A, BBB, BB, B, CCC). We have drawn a box around each cell where the spread required to compensate for default is wider than the tightest current spreads (as shown in Figure 39) of the relevant rating band across the currencies.
As has been the case in all the past versions of this study current IG spreads compensate for default for all previous 5-year default cycles seen since 1981. In fact at the tights it’s only BBBs (and mainly in EUR) that would have failed to exceed all past cohort compensation levels.
11 April 2016
Annual Default Study: Past the Point of No Return?
Deutsche Bank AG/London Page 25
Figure 40: Spreads Required to Compensate for Default Based on Global 5-year Cumulative Default Rates by Cohort
40% Recovery 0% Recovery
Cohort Year IG AA A BBB HY BB B CCC IG AA A BBB HY BB B CCC
1981 8 0 3 24 165 164 189 13 0 4 40 274 274 315
1982 11 0 8 26 232 221 225 471 19 0 14 44 386 369 375 784
1983 11 6 3 30 208 175 208 655 19 10 5 50 347 291 347 1,091
1984 10 5 3 27 259 173 313 750 16 8 5 44 432 288 522 1,250
1985 6 5 5 10 266 157 377 360 10 8 9 16 443 262 628 600
1986 13 5 8 32 238 104 334 631 21 8 13 53 397 173 557 1,052
1987 22 5 15 51 272 140 285 921 36 8 24 85 453 233 476 1,535
1988 15 5 10 34 304 151 350 923 25 8 16 56 507 251 583 1,538
1989 10 0 0 35 351 184 403 1,108 17 0 0 59 586 306 672 1,846
1990 8 0 0 26 354 148 436 1,630 13 0 0 43 590 246 726 2,717
1991 5 0 3 13 277 70 367 1,031 9 0 5 21 462 117 611 1,719
1992 2 0 3 4 150 25 208 657 4 0 5 7 249 41 347 1,095
1993 2 0 3 3 133 50 198 462 4 0 5 6 222 83 330 769
1994 3 0 3 7 137 58 198 772 6 0 5 11 228 96 330 1,286
1995 8 0 0 21 144 85 174 831 13 0 0 35 240 142 290 1,385
1996 8 0 3 18 170 91 245 404 13 0 4 30 283 152 408 674
1997 15 0 7 29 264 141 370 1,292 25 0 12 48 439 235 616 2,154
1998 31 0 13 58 397 219 543 1,698 52 0 22 96 661 365 904 2,830
1999 32 0 13 60 492 265 648 1,891 54 0 21 100 820 442 1,080 3,152
2000 33 0 15 58 476 238 624 1,956 55 0 25 96 793 396 1,041 3,261
2001 36 0 10 63 446 208 566 2,205 60 0 17 105 744 347 944 3,675
2002 19 0 0 36 313 114 361 1,512 32 0 0 60 522 189 601 2,519
2003 4 0 0 8 164 50 165 1,000 7 0 0 13 274 83 274 1,667
2004 6 0 2 9 104 44 113 542 9 0 3 15 174 73 188 904
2005 13 0 2 22 157 85 193 542 22 0 3 37 262 141 321 903
2006 8 0 2 13 188 83 238 745 13 0 3 21 314 138 397 1,241
2007 6 0 0 10 218 92 278 925 9 0 0 17 363 154 464 1,542
2008 5 0 0 8 266 84 351 1,677 8 0 0 13 443 140 585 2,795
2009 1 0 0 1 262 48 299 2,017 1 0 0 2 436 80 499 3,361
2010 0 0 0 0 125 23 114 649 0 0 0 0 208 38 191 1,081
2011 1 0 2 0 121 38 133 763 1 0 4 0 201 63 222 1,272
Source: Deutsche Bank, S&P
As ever it’s the HY market that provides us with the more interesting analysis. We first note that while the latest 5-year cohort shows a pick-up from the previous year’s all-time lows (Figure 41) it still remains extremely low from an historical perspective. Therefore the spreads required to compensate for default for BBs (38-63bps) and single-Bs (133-222bps) are comfortably lower than the current spreads, particularly in light of the widening we have seen in credit spreads since we published last year.
In fact given the spread widening we’ve seen current BB and single-B spreads in both EUR and USD would compensate for any 5-year period within our analysis when assuming a 40% recovery. For CCCs this is not the case for the cohorts formed from 1998-2001 or 2008 and 2009.
When we look at the most extreme recovery assumption (0%) there is only one 5-year cohort (1999) where the spread required to compensate for BB default would have been wider than current spread levels. For single-Bs this is the case for the cohorts formed from 1998-2001. For CCCs there are obviously many more cohorts that required wider spreads than current levels to
Figure 41: BB and B 5yr Cumulative
Default Rates by Cohort
0%
10%
20%
30%
40%
50%
19
81
19
84
19
87
19
90
19
93
19
96
19
99
20
02
20
05
20
08
20
11
BB B
Source: Deutsche Bank, S&P
11 April 2016
Annual Default Study: Past the Point of No Return?
Page 26 Deutsche Bank AG/London
compensate for default, although 18 of them still required a tighter spread than the current USD CCC spread (1,553bps).
European cohorts The analysis so far has focused on global default rates. Although we think they should be entirely relevant given that, in theory, default rates for a particular rating band should be somewhat agnostic to the region of default we thought it would be interesting to provide some analysis focusing on European issuers only. The US data would naturally be very similar to the global data, given the dominance of US names amongst the rated issuers through time.
In Figure 42 we provide a table that looks at the spreads required to compensate for default for European issuers by cohort. Again we put a box around the cells where the required spread is wider than the current EUR spreads for the appropriate rating. Unsurprisingly current IG spreads comfortably compensate for the historical cohort compensation levels. In fact the results for Europe are very similar to the overall global results. It’s again when we look at HY that we get the more interesting picture. Whilst current BB spreads (421bps) are wide enough to compensate for all past periods assuming a 40% recovery, for single-Bs (716bps) the 1999 and 2001 cohorts would have required wider spreads than current levels. When we assume the extreme recovery scenario (0%) the 1999-2001 cohorts require a wider than current BB spread, which is also true for single-Bs with the addition of the 2002 cohort. We should note here that the market was very much in its infancy back in 1999 with the HY cohort containing just 49 issuers. Given that this was very much at the start of the default cycle it’s not too surprising that European HY defaults were exaggerated (compared to the global outcome), particularly in light of the general lack of diversification (heavily weighted towards TMT). This is a key reason why we tend to prefer to look at the global default picture as it provides us with a more robust base analysis through history.
Figure 42: Spreads Required to Compensate for Default Based on European 5-year Cumulative Default Rates by Cohort
40% Recovery 0% Recovery
Cohort Year IG AA A BBB HY BB B IG AA A BBB HY BB B
1999 17 0 13 51 626 383 818 28 0 21 84 1,044 638 1,364
2000 29 0 22 71 513 313 623 48 0 37 118 855 522 1,039
2001 29 0 10 72 650 312 945 48 0 16 121 1,084 519 1,575
2002 17 0 0 44 408 210 496 29 0 0 74 681 350 827
2003 3 0 0 9 168 68 118 6 0 0 14 280 113 197
2004 3 0 0 8 94 37 99 6 0 0 14 157 62 165
2005 7 0 0 16 82 31 131 11 0 0 26 137 52 218
2006 3 0 0 8 112 16 176 6 0 0 13 186 27 293
2007 3 0 0 7 161 69 217 5 0 0 12 269 114 362
2008 3 0 0 7 237 118 343 5 0 0 12 395 197 572
2009 0 0 0 0 231 88 276 0 0 0 0 385 146 459
2010 0 0 0 0 126 37 206 0 0 0 0 210 61 343
2011 0 0 0 0 145 15 215 0 0 0 0 242 26 358
Source: Deutsche Bank, S&P
Overall the main takeaway here is that the spread widening that we have seen over the past year has pushed us to levels where we would likely be compensated for default over the cycle, particularly if past observations are anything to go by. Indeed if we remain in the low default environment that has been the norm for the past decade or more than it’s fair to say that spreads look very attractive at current levels for longer-term more buy-and-hold focused investors. We would also add here that individual issuer credit
11 April 2016
Annual Default Study: Past the Point of No Return?
Deutsche Bank AG/London Page 27
analysis could potentially further mitigate risks over the cycle and therefore we could argue current levels could be seen as a good entry point even if we do see a more general pick-up in defaults in the next year or so.
Default-compensation spreads for broad cash and CDS indices
We introduce a new methodology to gauge whether current credit spreads for broad indices provide sufficient compensation for potential defaults. In particular, we calculate what spread on a current index would be necessary to compensate for the default experience of individual historical rating cohorts, given the distribution of ratings in the current index. For short, we call them default-compensation spreads.
Plotting the default-compensation spreads for each annual historical cohort then illustrates the variation of default losses for the current index that would have occurred across past credit cycles. It is apparent that this finer methodology provides a better insight into the adequacy of current spreads than merely considering average historical default rates over the entire period, because it allows us to focus on stages of past default cycles that we believe are applicable to today’s default outlook.
In our methodology for cash bond indices, we calculate default-compensation spreads for each individual bond, given its time to workout/maturity and its rating’s historical default rates over such time periods starting at different points in the past. We then calculate the default-compensation spread for the broad index as the market-value-weighted average of default-compensation spreads for individual bonds.
While using actual historical default rates, we produce default-compensation spreads for a range of recovery assumptions at each seniority level. Throughout, we provide values for baseline, stressed and super-stressed recovery rates. The baseline recoveries are 60% for secured, 40% for senior unsecured and 20% for subordinated bonds. The stressed recoveries are 40% for secured, 20% for senior unsecured and 0% for subordinated bonds. The super-stressed recoveries are zero at all seniority levels.
This is shown in Figure 43-Figure 48. The dark blue bars represent our baseline recovery scenario. The lighter colours provide more pessimistic scenarios. Each chart with default-compensation spreads for a given index is overlaid with the current market spreads for the index. In particular, we use the benchmark spread (full horizontal line) and the asset swap spread (dashed horizontal line). Normally, we would consider the benchmark spread as the relevant level to compare default-compensation spreads to. However, we add the asset swap spread for completeness, if only to illustrate the difference between the EUR market and USD/GBP market. In the latter, government benchmark bonds have negative swap spreads and so the asset swap spread on the IG indices is actually higher than the benchmark spread.
The gap between the relevant spread line and default-compensation spread for a given historical cohort equals the default spread premium, i.e. the excess spread on the current index over and above what would be required should the default experience of each rating category be the same as it was for that historical cohort.
There is a clear (and well-known) pattern. The default-compensation spreads for IG indices are significantly lower than current market spreads. Most of their spread premium is a reward for taking on mark-to-market and liquidity risk
11 April 2016
Annual Default Study: Past the Point of No Return?
Page 28 Deutsche Bank AG/London
rather than default risk. This is different for high-yield indices where the current spread levels may or may not be attractive depending on our belief about today’s stage of the credit cycle.
Figure 43: iBoxx EUR: Corp. Non-fin. IG bond index Figure 44: DBIQ EUR HY bond index
0
50
100
150
1981
1982
1983
1984
1985
1986
1987
1988
1989
1990
1991
1992
1993
1994
1995
1996
1997
1998
1999
2000
2001
2002
2003
2004
2005
2006
2007
2008
2009
2010
2011
2012Sp
read
to
co
ver
his
tori
cal d
efau
lt r
ates
(b
p)
Historical cohort
Recovery rates: 60% secured, 40% senior unsecured, 20% subordinatedRecovery rates: 40% secured, 20% senior unsecured, 0% subordinatedRecovery rates: 0% secured, 0% senior unsecured, 0% subordinatedIndex benchmark spread (6 Apr 2016)Index asset swap spread (6 Apr 2016)
0
200
400
600
800
1,000
1,200
19
81
19
82
19
83
19
84
19
85
19
86
19
87
19
88
19
89
19
90
19
91
19
92
19
93
19
94
19
95
19
96
19
97
19
98
19
99
20
00
20
01
20
02
20
03
20
04
20
05
20
06
20
07
20
08
20
09
20
10
20
11
20
12Sp
read
to
co
ver
his
tori
cal d
efau
lt r
ates
(b
p)
Historical cohort
Recovery rates: 60% secured, 40% senior unsecured, 20% subordinatedRecovery rates: 40% secured, 20% senior unsecured, 0% subordinatedRecovery rates: 0% secured, 0% senior unsecured, 0% subordinatedIndex benchmark spread (6 Apr 2016)Index asset swap spread (6 Apr 2016)
Source: Deutsche Bank, S&P Source: Deutsche Bank, S&P
Figure 45: iBoxx GBP: Corp. Non-fin. IG bond index Figure 46: DBIQ GBP HY bond index
0
50
100
150
200
250
1981
1982
1983
1984
1985
1986
1987
1988
1989
1990
1991
1992
1993
1994
1995
1996
1997
1998
1999
2000
2001
2002
2003
2004
2005
2006
2007
2008
2009
2010
2011
2012Sp
read
to
co
ver
his
tori
cal d
efau
lt r
ates
(b
p)
Historical cohort
Recovery rates: 60% secured, 40% senior unsecured, 20% subordinatedRecovery rates: 40% secured, 20% senior unsecured, 0% subordinatedRecovery rates: 0% secured, 0% senior unsecured, 0% subordinatedIndex benchmark spread (6 Apr 2016)Index asset swap spread (6 Apr 2016)
0
200
400
600
800
1,000
1,200
19
81
19
82
19
83
19
84
19
85
19
86
19
87
19
88
19
89
19
90
19
91
19
92
19
93
19
94
19
95
19
96
19
97
19
98
19
99
20
00
20
01
20
02
20
03
20
04
20
05
20
06
20
07
20
08
20
09
20
10
20
11
20
12Sp
read
to
co
ver
his
tori
cal d
efau
lt r
ates
(b
p)
Historical cohort
Recovery rates: 60% secured, 40% senior unsecured, 20% subordinatedRecovery rates: 40% secured, 20% senior unsecured, 0% subordinatedRecovery rates: 0% secured, 0% senior unsecured, 0% subordinatedIndex benchmark spread (6 Apr 2016)Index asset swap spread (6 Apr 2016)
Source: Deutsche Bank, S&P Source: Deutsche Bank, S&P
Figure 47: iBoxx USD: Corp. Non-fin. IG bond index Figure 48: DBIQ USD HY bond index
0
50
100
150
200
1981
1982
1983
1984
1985
1986
1987
1988
1989
1990
1991
1992
1993
1994
1995
1996
1997
1998
1999
2000
2001
2002
2003
2004
2005
2006
2007
2008
2009
2010
2011
2012Sp
read
to
co
ver
his
tori
cal d
efau
lt r
ates
(b
p)
Historical cohort
Recovery rates: 60% secured, 40% senior unsecured, 20% subordinatedRecovery rates: 40% secured, 20% senior unsecured, 0% subordinatedRecovery rates: 0% secured, 0% senior unsecured, 0% subordinatedIndex benchmark spread (6 Apr 2016)Index asset swap spread (6 Apr 2016)
0
200
400
600
800
1,000
1,200
19
81
19
82
19
83
19
84
19
85
19
86
19
87
19
88
19
89
19
90
19
91
19
92
19
93
19
94
19
95
19
96
19
97
19
98
19
99
20
00
20
01
20
02
20
03
20
04
20
05
20
06
20
07
20
08
20
09
20
10
20
11
20
12Sp
read
to
co
ver
his
tori
cal d
efau
lt r
ates
(b
p)
Historical cohort
Recovery rates: 60% secured, 40% senior unsecured, 20% subordinatedRecovery rates: 40% secured, 20% senior unsecured, 0% subordinatedRecovery rates: 0% secured, 0% senior unsecured, 0% subordinatedIndex benchmark spread (6 Apr 2016)Index asset swap spread (6 Apr 2016)
Source: Deutsche Bank, S&P Source: Deutsche Bank, S&P
A small caveat in our calculations for cash bond indices is that we apply issuer-based default rates on bond-rating distributions, due to ease of complete data availability for the latter. Thus, we underestimate default probability for secured bonds and overestimate it for subordinated bonds that are part of the
11 April 2016
Annual Default Study: Past the Point of No Return?
Deutsche Bank AG/London Page 29
indices. Having done some sensitivity testing around this, we believe this has a fairly limited impact on the overall results, given the dominance of senior unsecured bonds in most of the indices.
Moreover, we can much more easily repeat the exercise for current CDS indices using issuer ratings throughout. CDS indices have the advantage of homogeneity in terms of maturities, seniority and equal weights of their constituents. Here, for each historical cohort, we calculate default-compensation spreads by simply replacing default probabilities in the CDS index pricing formula with the historical default paths in the relevant rating categories. We assume that unrated names have the average index rating (this applies to iTraxx Crossover only, with seven unrated names out of 75).
This is shown in Figure 49-Figure 52. Since 5Y CDS index spreads are a lot tighter than their cash counterparts above, the default spread premium is correspondingly smaller. In the Crossover/HY indices, there are cohorts whose default experience would render current spreads insufficient to cover default losses even with the baseline recovery levels.
Figure 49: iTraxx Main 5Y CDS index Figure 50: iTraxx Crossover 5Y CDS index
0
10
20
30
40
50
60
70
80
90
1981
1982
1983
1984
1985
1986
1987
1988
1989
1990
1991
1992
1993
1994
1995
1996
1997
1998
1999
2000
2001
2002
2003
2004
2005
2006
2007
2008
2009
2010
2011
2012
Spre
ad t
o c
ove
r h
isto
rica
l def
ault
rat
es (
bp
)
Historical cohort
Recovery rate: 40% Recovery rate: 20%
Recovery rate: 0% Market spread (6 Apr 2016)
0
200
400
600
800
1,000
1,200
1981
1982
1983
1984
1985
1986
1987
1988
1989
1990
1991
1992
1993
1994
1995
1996
1997
1998
1999
2000
2001
2002
2003
2004
2005
2006
2007
2008
2009
2010
2011
2012
Spre
ad t
o c
ove
r h
isto
rica
l def
ault
rat
es (
bp
)
Historical cohort
Recovery rate: 40% Recovery rate: 20%
Recovery rate: 0% Market spread (6 Apr 2016)
Source: Deutsche Bank, S&P Source: Deutsche Bank, S&P
Figure 51: CDX IG 5Y CDS index Figure 52: CDX HY 5Y CDS index
0
10
20
30
40
50
60
70
80
90
1981
1982
1983
1984
1985
1986
1987
1988
1989
1990
1991
1992
1993
1994
1995
1996
1997
1998
1999
2000
2001
2002
2003
2004
2005
2006
2007
2008
2009
2010
2011
2012
Spre
ad t
o c
ove
r h
isto
rica
l def
ault
rat
es (
bp
)
Historical cohort
Recovery rate: 40% Recovery rate: 20%
Recovery rate: 0% Market spread (6 Apr 2016)
0
200
400
600
800
1,000
1,200
1981
1982
1983
1984
1985
1986
1987
1988
1989
1990
1991
1992
1993
1994
1995
1996
1997
1998
1999
2000
2001
2002
2003
2004
2005
2006
2007
2008
2009
2010
2011
2012
Spre
ad t
o c
ove
r h
isto
rica
l def
ault
rat
es (
bp
)
Historical cohort
Recovery rate: 40% Recovery rate: 20%
Recovery rate: 0% Market spread (6 Apr 2016)
Source: Deutsche Bank, S&P Source: Deutsche Bank, S&P
While the Crossover/HY charts show that current spreads would have been insufficient to cover losses for a few past cohorts that experienced the most severe defaults (before the indices were launched in 2004), we show in the next section what the actual realised default rates and losses have been for the indices. They have been much milder, perhaps reflecting the fact that the selection process for index members tends to favour names that are less likely
11 April 2016
Annual Default Study: Past the Point of No Return?
Page 30 Deutsche Bank AG/London
to default than their respective rating categories. In any case, the available history is too short for any definitive confirmation of this hypothesis.
While HY credit obviously includes a much greater risk of negative excess returns than IG even for buy-and-hold investors, it also offers potentially much greater upside and overall higher expected returns. The fact that in relative terms default spread premia are much greater for IG than HY does not in and of itself constitute a relative value proposition. It merely reflects the fact that IG is much safer and therefore offers less upside.
As an additional caveat, we note that all the above default-compensation spreads are purely ratings based. While we use default histories for the S&P-rated universe, some bonds/issuers do not have an S&P rating at all. Throughout, we use the average ratings across the three agencies Moody’s, S&P and Fitch, or whichever subset of theirs is available.
Spread implied default rates
In this sub-section we update our analysis that looks to assess the value of current spread levels relative to defaults to try and identify where there might be value for the longer-term buy-and-hold-focused investor on a default risk adjusted basis. Essentially we look to calculate spread implied default rates as well as looking at default spread premiums (DSP), which we define as the difference between current spreads and the spread required to compensate for observed default. We first focus on the cash market before moving on to look at the CDS indices in both Europe and the US.
Cash market
Non-financial spread implied default rates Before we look at the results of this analysis we first give a brief description of the methodology. The analysis focuses on non-financials around the 5-year tenor. To achieve this we include all senior bonds with 4-6 years until maturity within the iBoxx indices. Having calculated average spreads for our sample bond sets we then use three different recovery assumptions (0%, 20% and 40%) to calculate implied default rates. We compare these default rates with an appropriate average five-year cumulative global default rate as well as the worst five-year periods observed since 1981. In addition we also provide the average and worst five-year level for the primary region of the various bond markets (Europe – EUR; UK – GBP; US – USD). We have highlighted the cells where the implied default rate is lower than the worst and average experience (darker blue) as well as those where the implied default rate is lower than the worst but higher than the average (lighter blue). The shading is based only on the historical global default rates.
We show the results of this analysis in Figure 54 but before we look at this in greater detail it’s worth noting that the outcome of this analysis has been significantly impacted by the widening in spreads we’ve seen since last year’s study. Figure 53 looks at spread histories for both IG and HY since 2010 with the dotted lines highlighting the moves over the past 12 months. Before the rally of the past month or so spreads had, in general, reached the widest levels since the European sovereign crisis. For the USD market we probably reached wider levels than we saw during the sovereign crisis. Since the end of March 2015 IG spreads have widened around 25-50bps (depending on currency) while EUR and USD HY have widened around 135bps and 200bps respectively.
11 April 2016
Annual Default Study: Past the Point of No Return?
Deutsche Bank AG/London Page 31
Figure 53: IG (left) and HY (right) Non-Financial Credit Spreads by Currency since 2010 (bps)
80
100
120
140
160
180
200
220
240
260
280
2010 2011 2012 2013 2014 2015 2016
EUR USD GBP
300
400
500
600
700
800
900
1,000
2010 2011 2012 2013 2014 2015 2016
EUR USD
Source: Deutsche Bank, Mark-it Group
So in light of the spread widening we’ve seen it’s not entirely surprising that spreads now imply default rates higher than average historical levels for all ratings and currencies, even assuming the worst recovery outcome (0%). For IG this remains the case even when we compare to the worst observed 5-year cumulative default rates. But this tends to be the case, so again it provides little surprise.
As ever the more interesting outcomes exist within the HY market. We can see that based on the 40% recovery assumption all HY rating bands imply a higher default rate than the worst observation. In fact this is the case for USD BBs even with the lowest recovery assumption but not for EUR BBs. It’s also worth noting that when we compare the implied default rates for EUR BBs with the worst observed European BB default rate, they are lower assuming the lower recovery assumptions (0%, 20%).
For single-Bs in both the EUR and USD markets implied default rates are lower than the worst observation when assuming the lower recoveries and for EUR single-Bs this is also true when comparing to the worst European single-B default and assuming a 40% recovery.
Finally looking at CCCs we can see that in the USD market implied defaults are between the historical average and worst assuming lower recoveries. EUR CCCs imply a default rate higher than the worst even at the lowest recovery although we should note that the index spread is heavily biased by the recent downgrade to CCC of Oi (Portugal Telecom).
11 April 2016
Annual Default Study: Past the Point of No Return?
Page 32 Deutsche Bank AG/London
Figure 54: Non-Financial 5-year Cumulative Spread Implied Default Rates Based on Different Recovery Assumptions
Actual 5yr Cumulative Default Rates
Implied 5yr Cumulative Default Rate Global Regional
5yr Spread 0% Recovery 20% Recovery 40% Recovery Worst Average Worst Average
EUR IG All 111 5.5% 6.7% 8.5% 2.9% 0.9% 2.4% 0.5%
AA 68 3.5% 4.3% 5.4% 0.5% 0.1% 0.0% 0.0%
A 90 4.4% 5.4% 6.8% 1.2% 0.4% 1.8% 0.2%
BBB 135 6.6% 8.0% 10.2% 5.1% 1.7% 5.8% 1.1%
HY All 585 24.8% 30.2% 38.5% 32.5% 17.0% 38.8% 13.4%
BB 427 18.9% 23.0% 29.4% 19.8% 8.3% 27.3% 6.0%
B 709 28.9% 35.1% 44.4% 40.0% 20.1% 47.6% 16.8%
CCC 2,526 68.9% 84.5% 99.0% 68.5% 49.4% 75.0% 41.6%
GBP IG All 165 8.0% 9.7% 12.1% 2.9% 0.9% 3.6% 0.6%
AA 63 2.9% 3.6% 4.7% 0.5% 0.1% 0.0% 0.0%
A 118 5.9% 7.1% 9.0% 1.2% 0.4% 3.3% 0.5%
BBB 210 10.1% 12.1% 15.1% 5.1% 1.7% 7.3% 1.0%
USD IG All 150 7.2% 8.8% 11.3% 2.9% 0.9% 2.4% 1.0%
AA 72 3.5% 4.3% 5.5% 0.5% 0.1% 0.5% 0.2%
A 101 4.9% 6.0% 7.7% 1.2% 0.4% 1.3% 0.4%
BBB 202 9.6% 11.7% 15.1% 5.1% 1.7% 4.2% 1.8%
HY All 761 31.7% 38.9% 49.9% 32.5% 17.0% 30.9% 17.4%
BB 473 21.1% 25.7% 32.7% 19.8% 8.3% 17.3% 8.4%
B 742 31.2% 38.0% 48.3% 40.0% 20.1% 38.4% 20.2%
CCC 1,522 53.0% 65.4% 83.2% 68.5% 49.4% 72.5% 50.8%
Source: Deutsche Bank, S&P, Mark-it Group
It certainly appears to be the case that current spread levels (even after the recent rebound) are pricing in fairly aggressive default rate outcomes over the next 5 years and in all likelihood current spreads would compensate the buy-and-hold investor for the extra risk they are taking on by moving down the rating spectrum. Perhaps the greater immediate worry and this might drive the near-term direction of credit spreads is whether we’re pricing in an aggressive outcome that is unlikely to materialize in the near-term (mainly due to intervention from authorities) or that we are likely to see a material rise in defaults sooner rather than later and then there still may actually be a far better entry point into credit markets, particularly at the lower end of the rating spectrum. We now turn our attention to default spread premiums to better evaluate relative value.
Non-financial default spread premiums1 While calculating implied default rates gives us a broad idea of whether credit prices in the type of default rates that have been observed historically they do not provide a sense of relative value across the credit spectrum. For that we use DSPs. These are calculated by subtracting the spread required to compensate for default, given a default and recovery assumption, from the index spread level. The default scenarios we have used within our analysis are the average 5-year cumulative default rates (based on data since 1981) as well as the worst observed 5-year period for each rating band since 1981. We also show the lowest 5-year default environment, particularly in light of the ultra low period for defaults that we have operated in for more than a decade now. For recoveries we have again used 0%, 20% and 40%. It should be noted that
1 Default spread premiums (DSP) for cash bonds calculated subtracting the spread required to
compensate for default for a given default and recovery assumption from the index spread level.
11 April 2016
Annual Default Study: Past the Point of No Return?
Deutsche Bank AG/London Page 33
the aim here is to provide a framework to assess which rating band provides the most attractive default adjusted spread from a buy-and-hold perspective.
We start by looking at EUR credit in Figure 55 and provide some of the key highlights below.
Based on an average default cycle HY DSPs are comfortably higher than IG DSPs even when we assume the lowest recovery (0%).
Although CCCs provide the widest DSP based on all default and recovery scenarios as we have already noted this is almost exclusively a consequence of the downgrade to CCC of Oi (Portugal Telecom) into a very small universe. Therefore we would not read too much into this opportunity.
The single-B DSP is wider than the BB DSP based on an average default cycle and 40% recovery but as we lower recovery assumptions then BBs provide a wider DSP than single-Bs.
As we look to the more extreme default scenarios BBs tend to offer the widest DSP, unless we assume the lowest recovery scenario.
If defaults remain very low it seems that it would pay to take risk down the rating spectrum even under the worst recovery assumption.
Figure 55: EUR Non-Financial Default Spread Premiums for Average, Best (lowest) and Worst (highest) 5-year
Cumulative Default Observations Assuming 40% (left), 20% (middle) and 0% (right) Recoveries
0
500
1,000
1,500
2,000
2,500
AA A BBB BB B CCC
Average Best Worst
-400
0
400
800
1,200
1,600
AA A BBB BB B CCC
Average Best Worst
-500
0
500
1,000
1,500
2,000
AA A BBB BB B CCC
Average Best Worst
Source: Deutsche Bank
The results for the analysis on the USD market are in Figure 56 and we provide the highlights below.
Based on an average default cycle and a 40% recovery DSPs widen as we move down the rating spectrum. As we lower the recovery assumption then the CCC DSP falls away. When assuming a 0% recovery the BB DSP is marginally wider than the single-B DSP and both are wider than the CCC DSP.
Based on the more aggressive default cycle BBs provide the widest DSP when assuming a 40% recovery but as we lower the recovery assumption the IG DSPs start to look more attractive with all IG rating bands wider than HY rating bands when assuming a 0% recovery.
As we saw with the EUR market, if we remain in a very low default environment it seems that it would pay to take risk down the rating spectrum even under the worst recovery assumption.
11 April 2016
Annual Default Study: Past the Point of No Return?
Page 34 Deutsche Bank AG/London
Figure 56: USD Non-Financial Default Spread Premiums for Average, Best (lowest) and Worst (highest) 5-year
Cumulative Default Observations Assuming 40% (left), 20% (middle) and 0% (right) Recoveries
0
200
400
600
800
1,000
1,200
AA A BBB BB B CCC
Average Best Worst
-400
-200
0
200
400
600
800
1,000
1,200
AA A BBB BB B CCC
Average Best Worst
-1,000
-500
0
500
1,000
AA A BBB BB B CCC
Average Best Worst
Source: Deutsche Bank
Overall the main conclusion in our view is that for an average default cycle assuming a 40% recovery then it looks like it pays to take risk, although we have noted some obvious issues surrounding EUR CCCs. As we assume the worst default scenarios BBs offer the widest DSPs unless we assume the lowest recoveries at which point IG DSPs are wider. We should also note here that the USD data used so far does not omit energy/commodity exposed names, which are generally trading at more stressed spread levels. In Figure 57 we rerun the analysis excluding these bonds for the average default cycle using the different recovery assumptions. We can see that whilst USD CCCs still have the widest DSP based on a 40% recovery as we lower the recovery assumption the DSP falls significantly and is in fact negative when assuming a 0% recovery. USD Single-Bs provide a wider DSP than USD BBs based on a 20% recovery but are marginally tighter when assuming a 0% recovery.
CDS market We now switch our focus to the CDS market. We again look to calculate the level of default implied by current spread levels as well as the DSP for the key CDS indices.
Rather than focusing purely on the 5-year tenor, we actually look at the various CDS indices (iTraxx and CDX) and calculate implied cumulative default rates across the term structure assuming different recovery levels. We then compare them with a rating implied default rate. In order to do this we have looked at the rating breakdown of each index looking at the issuer rating (not issue rating) for each constituent and then using average cumulative default rate data from S&P have calculated an average cumulative default probability based on the appropriate tenor. We should also note that when assessing the rating for each issuer we have used the average rating from Moody’s, S&P and Fitch (where available). For unrated issuers we have assumed the average HY cumulative default rate.
We have also again calculated DSPs for each index across the maturity spectrum assuming different recovery levels. For this we take the aforementioned rating implied default rate and calculate the spread required to compensate for default assuming different recoveries and subtract this from the actual trading level of the index. In addition we show the spread implied default count which is simply calculated by multiplying the spread implied default rate with the number of constituents in the index.
We show the results of the analysis in Figure 59, the shaded cells indicate where the spread implied default rate is lower than the rating implied rate and where the DSP is therefore negative. Essentially the highlighted cells show us where the longer-term buy-and-hold investor is not being compensated for the risk of average defaults over the tenor of the index.
Figure 57: USD DSP for Average
Defaults (0-40% Recoveries)
-200
-100
0
100
200
300
400
500
AA A BBB BB B CCC
40% 20% 0%
Source: Deutsche Bank
11 April 2016
Annual Default Study: Past the Point of No Return?
Deutsche Bank AG/London Page 35
As we saw with the cash market the most obvious development over the past 12 months has been that spreads are now wider than when we published our previous default study. We show this in Figure 58 where we look at the main benchmark on-the-run iTraxx and CDX series since 2010. Despite the spread tightening we’ve seen over the past couple of months we are still around 15-20bps wider in IG while iTraxx Crossover and CDX HY have widened by 54bps and 100bps respectively.
Figure 58: On-the-Run 5-year iTraxx (left) and CDX (right) Benchmark Indices since 2010
0
200
400
600
800
1,000
0
50
100
150
200
250
2010 2011 2012 2013 2014 2015 2016
iTraxx Main (LHS) iTraxx Crossover (RHS)
0
200
400
600
800
1,000
0
20
40
60
80
100
120
140
160
2010 2011 2012 2013 2014 2015 2016
CDX IG (LHS) CDX HY (RHS)
Source: Deutsche Bank, Bloomberg Finance LP
Looking now at the results in Figure 59 we can see that once again IG indices in both Europe and North America imply default rates higher than the rating implied levels even when we assume the most extreme recoveries. This reaffirms the reoccurring view within this note that for the buy-and-hold investor IG spreads seem to more than comfortably compensate investors for the risk of default, even when we assume some extreme outcomes.
Therefore, as usual, the main points of interest come from the HY indices. Given the 100bps of widening in the CDX HY index spread implied default rates are now higher than the rating implied rates at all tenors and even when we assume the lowest possible recoveries. For iTraxx Crossover this is true for all non-zero recoveries but when we assume a 0% recovery the spread implied default rate is lower than the rating implied rate at the 3-year and 5-year tenors.
11 April 2016
Annual Default Study: Past the Point of No Return?
Page 36 Deutsche Bank AG/London
Figure 59: CDS Index Spread and Rating Implied Default Rates/Count and Default Spread Premium
Spread Implied Cumulative DRs Default Spread Premium (bps) Spread Implied Cumulative Default Count
Index Family Index
Average Rating Tenor
Rating Implied Default Rate Spread
0% Recovery
20% Recovery
40% Recovery
0% Recovery
20% Recovery
40% Recovery
0% Recovery
20% Recovery
40% Recovery
iTraxx Main A- to BBB+ 3yr 0.3% 50 1.6% 2.0% 2.7% 41 43 45 2.0 2.5 3.3
5yr 1.1% 77 3.9% 4.9% 6.5% 56 60 65 4.9 6.1 8.1
7yr 1.4% 96 6.7% 8.3% 10.9% 77 81 85 8.4 10.4 13.7
10yr 2.3% 112 10.8% 13.3% 17.3% 89 94 98 13.5 16.6 21.7
Fin Sen A to A- 5yr 0.6% 98 5.0% 6.2% 8.1% 86 88 91 1.5 1.9 2.4
10yr 1.4% 124 11.9% 14.6% 19.0% 110 112 115 3.6 4.4 5.7
Fin Sub BBB+ to BBB 5yr 1.8% 227 11.1% 13.7% 17.9% 192 199 206 3.3 4.1 5.4
10yr 3.6% 257 23.0% 27.9% 35.4% 221 228 235 6.9 8.4 10.6
Crossover BB- to B+ 3yr 8.3% 243 7.5% 9.3% 12.2% -26 28 82 5.6 7.0 9.1
5yr 16.2% 317 15.2% 18.6% 24.0% -22 46 114 11.4 14.0 18.0
7yr 17.9% 352 22.4% 27.1% 34.4% 78 133 187 16.8 20.3 25.8
10yr 21.4% 370 31.5% 37.6% 46.7% 134 182 229 23.6 28.2 35.0
CDX IG BBB+ to BBB 3yr 0.4% 51 1.6% 2.0% 2.7% 39 41 44 2.0 2.5 3.3
5yr 1.4% 78 4.0% 4.9% 6.5% 51 56 62 5.0 6.2 8.2
7yr 1.8% 98 6.8% 8.5% 11.1% 73 78 83 8.6 10.6 13.9
10yr 2.9% 116 11.1% 13.7% 17.8% 87 93 98 13.9 17.1 22.3
HY BB- to B+ 3yr 8.8% 390 11.7% 14.5% 18.8% 101 159 217 11.7 14.5 18.8
5yr 17.1% 442 20.6% 25.0% 31.9% 83 155 227 20.6 25.0 31.9
7yr 18.9% 472 28.8% 34.6% 43.3% 182 240 298 28.8 34.6 43.3
10yr 22.8% 471 38.2% 45.2% 55.1% 218 268 319 38.2 45.2 55.1
Source: Deutsche Bank, Mark-it Group
We now move our attention to the DSPs, which as we mentioned when looking at the cash market are a better way of assessing relative value (from a buy-and-hold perspective) between indices. We have already shown the actual values in Figure 59, in Figure 60 we chart the DSPs for the 5-year indices assuming different recoveries. The chart provides us with slightly contrasting stories between Europe and North America. For the CDX indices the HY index provides a wider DSP based on all recovery assumptions. In Europe the Fin Sub index provides us with such an outcome although we are mindful of the relatively limited trading activity in this index as well as how valid the generally senior issuer ratings we’ve used to assess historical default probabilities are. That said when comparing Main and Crossover we can see that while the Crossover DSP (114bps) is comfortably wider than the Main DSP (65bps) assuming a 40% recovery, as soon as we lower the recovery assumption the DSP on Main is wider than the Crossover DSP. In fact at a 0% recovery the Crossover DSP is negative.
The overriding story is that IG indices, as ever, comfortably compensate for average defaults. However while this is also the case for CDX HY, it is not the case for iTraxx Crossover, which could be argued to be at fairly stretched levels based on an average default cycle but with low recoveries. This contrast is not entirely surprising given that the average rating and rating implied default rate of CDX HY is similar to iTraxx Crossover but CDX HY is around 125bps wider. It could be argued that the extra spread available for the CDX index reflects potential contagion from energy/commodity exposed names, however from a buy-and-hold perspective the extra spread on offer in CDX HY provides the buffer of protection against average defaults.
11 April 2016
Annual Default Study: Past the Point of No Return?
Deutsche Bank AG/London Page 37
Figure 60: Benchmark iTraxx and CDX Index 5-year DSPs Assuming Different
Recoveries (bps)
-50
0
50
100
150
200
250
Main Non-Fin Fin Sen Fin Sub Crossover IG HY
iTraxx CDX
0% Recovery 20% Recovery 40% Recovery
Source: Deutsche Bank
LT average default rates vs. actual default rates We have highlighted that iTraxx Crossover is not pricing in average defaults assuming very low recoveries. However we could also question the validity of these average default levels based on what we have seen historically. Figure 61 updates our analysis from last year assessing actual cumulative default and loss rates for each series of the iTraxx Crossover and CDX HY indices. We have only tracked these indices up to the maturity of the 5-year tenor. We can see that historically the worst 5-year cumulative default rate we have seen for Crossover is 12%, which is more than 4% below the average level implied by the rating distribution of the index. So even at the height of the GFC defaults fell someway short of our calculated average levels. Admittedly the index was probably slightly better rated at this point, which could have an impact. But theoretically we are talking about the worst point in the cycle here, not the average. So from that perspective our rating implied default rates could be considered a little too conservative.
Figure 61: Actual Cumulative Default/Loss Rates for the iTraxx Crossover (left) and CDX HY (right) Indices by Series
0%
2%
4%
6%
8%
10%
12%
14%
S1
(5
.2yrs
)S
2 (5
.5yrs
)S
3 (5
.2yrs
)S
4 (5
.2yrs
)S
5 (5
.3yrs
)S
6 (5
.2yrs
)S
7 (5
.3yrs
)S
8 (5
.3yrs
)S
9 (5
.3yrs
)S
10
(5
.2yrs
)S
11
(5
.3yrs
)S
12
(5
.2yrs
)S
13
(5
.2yrs
)S
14
(5
.2yrs
)S
15
(5
.0yrs
)S
16
(4
.5yrs
)S
17
(4
.0yrs
)S
18
(3
.5yrs
)S
19
(3
.0yrs
)S
20
(2
.5yrs
)S
21
(2
.0yrs
)S
22
(1
.5yrs
)S
23
(1
.0yrs
)S
24
(0
.5yrs
)S
25
(0
.0yrs
)
Default Rate Loss Rate
0%2%4%6%8%
10%12%14%16%18%20%
S1
(5
.4yrs
)S
2 (5
.5yrs
)S
3 (5
.4yrs
)S
4 (5
.2yrs
)S
5 (5
.2yrs
)S
6 (5
.2yrs
)S
7 (5
.2yrs
)S
8 (5
.2yrs
)S
9 (5
.2yrs
)S
10
(5
.2yrs
)S
11
(5
.2yrs
)S
12
(5
.3yrs
)S
13
(5
.2yrs
)S
14
(5
.2yrs
)S
15
(5
.2yrs
)S
16
(5
.0yrs
)S
17
(4
.5yrs
)S
18
(4
.0yrs
)S
19
(3
.5yrs
)S
20
(3
.0yrs
)S
21
(2
.5yrs
)S
22
(2
.0yrs
)S
23
(1
.5yrs
)S
24
(1
.0yrs
)S
25
(0
.5yrs
)S
26
(0
.0yrs
)
Default Rate Loss Rate
Source: Deutsche Bank
Looking at the same analysis for CDX HY we can see that our calculated rating implied default rate (17.1%) is lower than the worst 5-year experience (18%), but only just. So again we could argue that our average rates are on the conservative side. Furthermore for CDX HY we have already highlighted that we comfortably price in the average default rate and on this basis would also price in the worst historical experience.
One final point to note about this analysis is that loss rates are not that much lower than the default rates, which suggests recoveries have also tended to be lower than the considered average levels of around 40%. So we would make the assertion that it may be necessary to focus on the results assuming lower recovery levels.
11 April 2016
Annual Default Study: Past the Point of No Return?
Page 38 Deutsche Bank AG/London
Appendix – Methodology, Raw Data and Calculations
Now we have gone through the conclusions we will spend a little time going through the methodology and the raw data. The spread required to compensate for default is calculated using the expected loss for each rating band given historical default and different assumed recoveries. The starting point for such calculations is the rating agencies’ historical databases on default. In this report, we have previously concentrated on Moody’s default data but this year we have switched to using S&P data as it enabled us to focus purely on non-financial defaults as well as the option to look at defaults on a regional basis, although much of our analysis focuses on the global numbers.
The data from S&P covers the period from 1981-2015. In Figure 62 and Figure 63 we compare the average cumulative default rates from S&P with an equivalent average cumulative default rates from Moody’s (based on data from 1983-2015). There are some obvious differences, particularly with the highest ratings, although at these ratings the default levels we are talking about are still very low in absolute terms. For the more interesting rating bands BBB-B the default rates are more similar, particularly out to the 5-year point, which is broadly where the average life of the HY market in both Europe and the US sits.
Figure 62: S&P vs. Moody’s Average Cumulative IG Default Rates – AA (left), A (middle) and BBB (right)
0.0%
0.5%
1.0%
1.5%
2.0%
2.5%
1 4 7 10 13 16 19
Years
S&P Moody's
0%
1%
2%
3%
4%
5%
6%
7%
1 4 7 10 13 16 19
Years
S&P Moody's
0%
2%
4%
6%
8%
10%
12%
1 4 7 10 13 16 19
Years
S&P Moody's
Source: Deutsche Bank, Moody’s, S&P
Figure 63: S&P vs. Moody’s Average Cumulative HY Default Rates – BB (left), B (middle) and CCC (right)
0%
5%
10%
15%
20%
25%
30%
1 4 7 10 13 16 19
Years
S&P Moody's
0%
10%
20%
30%
40%
50%
60%
1 4 7 10 13 16 19
Years
S&P Moody's
0%
10%
20%
30%
40%
50%
60%
70%
1 4 7 10 13 16 19
Years
S&P Moody's
Source: Deutsche Bank, Moody’s, S&P
US vs. Europe cumulative default rates
In Figure 64-Figure 66 we show a number of charts comparing cumulative default rates for European issuers with those of US issuers. The main point to note here is that in general average historical European default rates have been lower. This is probably in large part due to the fact that there is not so much history for rated European issuers. Based on the S&P database there
11 April 2016
Annual Default Study: Past the Point of No Return?
Deutsche Bank AG/London Page 39
has only been more than 100 European IG rated issuers since 1995 and only since 2004 for HY. Therefore most of the relevant data for Europe occurs during the past decade or so of extremely low defaults and therefore probably helps explain the lower default rates relative to the more developed US market. This is also why we have focused on the global numbers for much of our analysis.
Figure 64: S&P Average Cumulative IG (left) and HY (right) Default Rates
0%
1%
2%
3%
4%
5%
6%
1 6 11 16 21
Years
Global US Europe
0%
5%
10%
15%
20%
25%
30%
35%
1 6 11 16 21
Years
Global US Europe
Source: Deutsche Bank, S&P
Figure 65: S&P Average Cumulative AA (left) A (middle) and BBB (right) Default Rates
0.0%
0.5%
1.0%
1.5%
2.0%
1 6 11 16 21
Years
Global US Europe
0%
1%
2%
3%
4%
5%
1 6 11 16 21
Years
Global US Europe
0%
2%
4%
6%
8%
10%
1 6 11 16 21
Years
Global US Europe
Source: Deutsche Bank, S&P
Figure 66: S&P Average Cumulative BB (left) B (middle) and CCC (right) Default Rates
0%
5%
10%
15%
20%
25%
1 6 11 16 21
Years
Global US Europe
0%
5%
10%
15%
20%
25%
30%
35%
40%
1 6 11 16 21
Years
Global US Europe
0%
10%
20%
30%
40%
50%
60%
70%
1 6 11 16 21
Years
Global US Europe
Source: Deutsche Bank, S&P
How we calculate spreads required to compensate for default probability?
It needs to be highlighted that the spreads calculated are spreads based on the maturity of the indices. That would imply we need to calculate the spreads required to compensate the cumulative default probabilities over that time period. The formula we use assumes constant instantaneous hazard rate, which is determined by the spread to that maturity. We then integrate the
11 April 2016
Annual Default Study: Past the Point of No Return?
Page 40 Deutsche Bank AG/London
continuously compounded survival probability to get the cumulative survival probability over time. As such, the formula can be used to calculate the spread from cumulative default probability or vice versa. We get the cumulative default probabilities from the Moody’s database and calculate the compensation spreads from them.
)1/(1 RSTeD
where D is the cumulative default probability over time T and S is the Spread to that maturity and R is the recovery
Solving for spread S,
)1ln()1(
DT
RS
We should note here that some of our analysis uses different calculations where it makes more sense to look at the path of defaults rather than simply assuming a constant instantaneous hazard rate.
Recovery rates
In terms of recovery we have used a selection of different rates throughout the note, generally focusing on 0%, 20% and 40%. However in Figure 67 (for comparison purposes) we publish a table showing average senior unsecured recovery rates for different rating bands. Recovery rates can fluctuate depending on different macroeconomic backdrops, which is why we include the range of different recovery scenarios. Recoveries are a very important factor when trying to assess losses in the case of default and therefore calculate the spread required to compensate for default.
Figure 67: Moody’s Senior Unsecured Recovery Rates by Rating (1983-2015)
Year 1 Year 2 Year 3 Year 4 Year 5 Average
Aaa 3.3% 3.3% 61.9% 69.6% 34.5%
Aa 37.2% 39.0% 38.1% 44.0% 43.2% 40.3%
A 30.4% 42.6% 45.0% 44.5% 44.2% 41.3%
Baa 42.9% 44.4% 44.6% 44.6% 44.4% 44.2%
Ba 44.5% 43.5% 42.6% 42.3% 42.4% 43.1%
B 37.6% 36.6% 36.9% 37.3% 37.9% 37.3%
Caa-C 38.0% 38.4% 38.4% 38.9% 39.0% 38.5%
IG 40.0% 43.5% 44.4% 44.6% 44.4% 43.4%
HY 38.3% 38.1% 38.2% 38.6% 39.0% 38.4%
All 38.3% 38.4% 38.7% 39.2% 39.5% 38.8% Source: Moody’s
11 April 2016
Annual Default Study: Past the Point of No Return?
Deutsche Bank AG/London Page 41
Spreads required to compensate for default
Figure 68: Spreads Required to Compensate for Default Assuming Different Recovery Levels
40% Recovery 20% Recovery 0% Recovery
Years IG AA A BBB HY BB B CCC IG AA A BBB HY BB B CCC IG AA A BBB HY BB B CCC
1 5 0 2 10 253 45 248 1,860 7 0 2 13 337 60 331 2,479 9 0 3 16 422 75 413 3,099
2 7 0 2 14 256 73 293 1,391 10 0 3 18 341 98 390 1,854 12 0 4 23 427 122 488 2,318
3 8 1 3 15 249 90 298 1,120 11 1 3 21 332 121 397 1,493 14 1 4 26 416 151 497 1,867
4 10 1 3 18 237 99 287 940 13 1 5 25 316 132 382 1,254 16 2 6 31 395 166 478 1,567
5 11 1 4 21 223 104 270 817 15 2 6 28 298 138 360 1,089 18 2 7 34 372 173 450 1,361
6 12 2 5 22 209 105 253 701 16 2 7 30 279 141 337 935 20 3 8 37 349 176 422 1,168
7 13 2 6 23 197 105 237 619 17 3 8 31 262 140 316 825 21 3 10 39 328 175 395 1,031
8 13 2 7 24 185 103 221 552 18 3 9 31 246 137 295 736 22 3 11 39 308 172 369 920
9 14 2 7 24 174 101 208 506 18 3 10 32 232 134 277 674 23 3 12 40 290 168 346 843
10 14 2 8 24 165 98 196 464 18 3 10 32 220 131 262 619 23 4 13 40 275 163 327 773
11 14 2 8 24 156 95 185 430 19 3 11 33 208 126 247 573 23 4 14 41 261 158 309 716
12 14 2 9 24 148 91 175 403 19 3 11 32 198 121 234 538 23 4 14 40 247 152 292 672
13 14 2 9 24 141 88 166 382 18 3 12 32 188 117 222 510 23 4 15 40 235 146 277 637
14 14 3 9 23 134 84 158 362 18 3 12 31 179 112 211 482 23 4 15 39 224 140 264 603
15 14 3 9 23 129 81 151 338 18 3 12 31 172 109 202 450 23 4 15 38 214 136 252 563
16 14 3 9 23 123 79 144 320 18 4 12 31 164 105 193 426 23 4 15 38 205 131 241 533
17 14 3 10 23 118 76 138 302 18 4 13 31 157 101 184 403 23 5 16 38 196 127 230 504
18 14 3 10 23 113 74 132 286 18 4 14 31 151 98 176 381 23 5 17 38 188 123 220 476
19 14 3 11 23 109 72 127 271 19 4 14 31 145 96 169 361 23 5 18 38 181 120 211 451
20 14 4 11 23 105 71 122 257 19 5 15 30 140 94 162 343 23 6 18 38 175 118 203 429
Source: Deutsche Bank, S&P
Figure 69: IG Spread Required to Compensate for Default Assuming a 40% (left), 20% (middle) and 0% (right) Recovery
0
5
10
15
20
25
30
1 4 7 10 13 16 19
Years
IG AA A BBB
0
5
10
15
20
25
30
35
1 4 7 10 13 16 19
Years
IG AA A BBB
0
10
20
30
40
50
1 4 7 10 13 16 19
Years
IG AA A BBB
Source: Deutsche Bank, S&P
Figure 70: HY Spread Required to Compensate for Default Assuming a 40% (left), 20% (middle) and 0% (right)
Recovery
0
50
100
150
200
250
300
350
1 4 7 10 13 16 19
Years
HY BB B
0
100
200
300
400
500
1 4 7 10 13 16 19
Years
HY BB B
0
100
200
300
400
500
600
1 4 7 10 13 16 19
Years
HY BB B
Source: Deutsche Bank, S&P
11 April 2016
Annual Default Study: Past the Point of No Return?
Page 42 Deutsche Bank AG/London
Credit trading levels against spreads required to compensate for default
Whilst we have formed most of our conclusions in earlier sections of this note the following section takes a more detailed graphical look at the spreads required to compensate for default probability assuming different recovery rates against historical index level spreads. We also include here a fuller compilation of default spread premium charts.
The charts focus on non-financial indices across the rating bands. We include charts for the EUR, USD and GBP markets for IG and EUR and USD for the HY market. We initially show the spread histories compared to the spread required to compensate for average historical default based on the appropriate rating and index average life, assuming both a 40% and 0% recovery. We then show the DSP charts where we subtract the spread required to compensate for default from the actual trading levels. For this we only use the analysis where we assume a 40% recovery.
Investment Grade
Figure 71: EUR AA (left), A (middle) and BBB (right) Index Spread Histories vs. Default-Compensation Spreads (bps)
0
50
100
150
200
250
1999 2001 2004 2006 2009 2011 2014
AA 40% 0%
0
50
100
150
200
250
300
350
1999 2001 2004 2006 2009 2011 2014
A 40% 0%
0
100
200
300
400
500
600
1999 2001 2004 2006 2009 2011 2014
BBB 40% 0%
Source: Deutsche Bank
Figure 72: USD AA (left), A (middle) and BBB (right) Index Spread Histories vs. Default-Compensation Spreads (bps)
0
50
100
150
200
250
300
350
1999 2001 2004 2006 2009 2011 2014
AA 40% 0%
0
100
200
300
400
500
1999 2001 2004 2006 2009 2011 2014
A 40% 0%
0
100
200
300
400
500
600
700
1999 2001 2004 2006 2009 2011 2014
BBB 40% 0%
Source: Deutsche Bank
Figure 73: GBP AA (left), A (middle) and BBB (right) Index Spread Histories vs. Default-Compensation Spreads (bps)
0
50
100
150
200
250
1999 2001 2004 2006 2009 2011 2014
AA 40% 0%
0
50
100
150
200
250
300
350
1999 2001 2004 2006 2009 2011 2014
A 40% 0%
0
100
200
300
400
500
600
1999 2001 2004 2006 2009 2011 2014
BBB 40% 0%
Source: Deutsche Bank
11 April 2016
Annual Default Study: Past the Point of No Return?
Deutsche Bank AG/London Page 43
Figure 74: AA (left), A (middle) and BBB (right)Default Spread Premium (bps)
0
50
100
150
200
250
300
350
1999 2001 2004 2006 2009 2011 2014
EUR USD GBP
0
100
200
300
400
500
1999 2001 2004 2006 2009 2011 2014
EUR USD GBP
0
100
200
300
400
500
600
700
1999 2001 2004 2006 2009 2011 2014
EUR USD GBP
Source: Deutsche Bank
High Yield
Figure 75: EUR BB (left), B (middle) and CCC (right) Index Spread Histories vs. Default-Compensation Spreads (bps)
0
200
400
600
800
1,000
1,200
1,400
1,600
2003 2004 2006 2008 2010 2012 2014
BB 40% 0%
0
500
1,000
1,500
2,000
2,500
3,000
2003 2004 2006 2008 2010 2012 2014
B 40% 0%
0
1,000
2,000
3,000
4,000
5,000
6,000
2003 2004 2006 2008 2010 2012 2014
CCC 40% 0%
Source: Deutsche Bank, Mark-it Group
Figure 76: USD BB (left), B (middle) and CCC (right) Index Spread Histories vs. Default-Compensation Spreads (bps)
0
200
400
600
800
1,000
1,200
1,400
1988 1992 1996 2000 2004 2008 2012
BB 40% 0%
0
500
1,000
1,500
2,000
1988 1992 1996 2000 2004 2008 2012
B 40% 0%
0
500
1,000
1,500
2,000
2,500
3,000
3,500
2000 2002 2004 2007 2009 2011 2014
CCC 40% 0%
Source: Deutsche Bank
Figure 77: BB (left), B (middle) and CCC (right)Default Spread Premium (bps)
0
200
400
600
800
1,000
1,200
1,400
1988 1992 1996 2000 2004 2008 2012
EUR USD
-500
0
500
1,000
1,500
2,000
2,500
1988 1992 1996 2000 2004 2008 2012
EUR USD
-1,000
0
1,000
2,000
3,000
4,000
5,000
2000 2002 2004 2007 2009 2011 2014
EUR USD
Source: Deutsche Bank, Mark-it Group
11 April 2016
Annual Default Study: Past the Point of No Return?
Page 44 Deutsche Bank AG/London
Why additional spread is required above that required to compensate for default
This piece has only ever aimed to look at the spread required to compensate for default. In effect it is the first building block in assessing where credit should trade as defaults are the only way a buy-and-hold investor actually loses money in credit relative to the risk free investment. In reality there are other important factors that need to be taken into consideration. The unparalleled volatility and stress in credit markets post crisis should be testament to why additional protection is perhaps needed over and above pure default risk. However trying to put a number to this becomes increasingly subjective and open to interpretation. For those wanting to explore further, these are some of the factors that need to be considered for those not buying and holding to maturity.
Liquidity While credit has always tended to be less liquid than government bonds (there were countries where this was not the case post the sovereign crisis) it could be argued this issue continues to gain increased importance largely due to the evolving regulatory environment and significant intervention in recent years. In Figure 78 we show the outstanding size of the US corporate bond market relative to the size of dealer’s inventory of corporate bonds, a series that was in negative territory at one point in the past 12 months.
Figure 78: Outstanding US Corporate Bond Market vs. US Dealer’s Inventory
($bn)
0
50
100
150
200
250
0
1,000
2,000
3,000
4,000
5,000
6,000
7,000
8,000
9,000 Outstanding US Corporate Bons (LHS)
US Dealer's Inventory of Corporate Bonds (RHS)
New inventory series since 2013
Source: Deutsche Bank, SIFMA, Federal Reserve Bank of New York
QE across the globe has forced investors further down the yield curve by artificially lowering Government bond yields and thus helping the credit market to grow. At the same time regulation has forced banks to hold less inventory thus creating an imbalance and risks that liquidity could completely disappear if we were to see a specific negative credit event. This would likely exacerbate the fact that liquidity generally tends to reduce in times of increased volatility.
The problem for investors is that they are unlikely to be able to price much of this illiquidity risk as the pressure to outperform short-term targets doesn’t encourage a risk/reward approach to liquidity. Experience tells us that liquidity is unlikely to be priced in properly until it’s needed. So the current dynamics of
11 April 2016
Annual Default Study: Past the Point of No Return?
Deutsche Bank AG/London Page 45
the market might make the next negative credit cycle more severe than the fundamentals suggest.
Return over risk-free alternative Clearly one does not invest in credit to only get a return equal to the risk-free (i.e. government bonds). We need additional spread for it to be worth holding credit on a risk-reward basis.
What is the risk-free these days? The Sovereign crisis severely compromised the notion of a risk-free rate to benchmark credit. However in 3-4 years we’ve gone from high Sovereign risk and high yields to one where more and more Government markets are tending towards negative yields as aggressive central bank intervention dominates. So investors have had to question the suitability of government credit benchmarks from both extremes over the past few years. This makes it very difficult to assess relative risk.
Cost of credit investing Clearly the further you move along the credit curve the more intensive you need to be in analysing credit. Therefore the cost base is higher and requires a higher reward than simply that compensating you for default risk. Management fees also have to be paid out of returns.
Ratings transition risk Some investors can only own bonds down to a certain rating category and may be forced sellers if a bond is downgraded through this lower limit. So we probably need a premium for risk of downward rating migration, especially in these troubled times.
Uncertainty and timing of recovery rate In an event of default the amount and timing of recovery is uncertain.
Short-term performance targets Investment grade rarely fails to compensate for default risk over the medium to long run, but investors are increasingly measured on a short-term basis. They therefore need some cushion to protect against mark-to-market volatility.
Quantifying these factors is outside the remit of this report. The buy-and-hold investor has less need to worry about them though. Hopefully this report should help show the crucial default building block that credit spreads are built around.
11 April 2016
Annual Default Study: Past the Point of No Return?
Page 46 Deutsche Bank AG/London
Appendix 1
Important Disclosures
Additional information available upon request
*Prices are current as of the end of the previous trading session unless otherwise indicated and are sourced from local exchanges via Reuters, Bloomberg and other vendors . Other information is sourced from Deutsche Bank, subject companies, and other sources. For disclosures pertaining to recommendations or estimates made on securities other than the primary subject of this research, please see the most recently published company report or visit our global disclosure look-up page on our website at http://gm.db.com/ger/disclosure/DisclosureDirectory.eqsr
Analyst Certification
The views expressed in this report accurately reflect the personal views of the undersigned lead analyst(s). In addition, the undersigned lead analyst(s) has not and will not receive any compensation for providing a specific recommendation or view in this report. Jim Reid/Nick Burns/Michal Jezek/Sukanto Chanda/Oleg Melentyev/Daniel Sorid
(a) Regulatory Disclosures
(b) 1.Important Additional Conflict Disclosures
Aside from within this report, important conflict disclosures can also be found at https://gm.db.com/equities under the "Disclosures Lookup" and "Legal" tabs. Investors are strongly encouraged to review this information before investing.
(c) 2.Short-Term Trade Ideas
Deutsche Bank equity research analysts sometimes have shorter-term trade ideas (known as SOLAR ideas) that are consistent or inconsistent with Deutsche Bank's existing longer term ratings. These trade ideas can be found at the SOLAR link at http://gm.db.com.
11 April 2016
Annual Default Study: Past the Point of No Return?
Deutsche Bank AG/London Page 47
(d) Additional Information
The information and opinions in this report were prepared by Deutsche Bank AG or one of its affiliates (collectively
"Deutsche Bank"). Though the information herein is believed to be reliable and has been obtained from public sources
believed to be reliable, Deutsche Bank makes no representation as to its accuracy or completeness.
If you use the services of Deutsche Bank in connection with a purchase or sale of a security that is discussed in this
report, or is included or discussed in another communication (oral or written) from a Deutsche Bank analyst, Deutsche
Bank may act as principal for its own account or as agent for another person.
Deutsche Bank may consider this report in deciding to trade as principal. It may also engage in transactions, for its own
account or with customers, in a manner inconsistent with the views taken in this research report. Others within
Deutsche Bank, including strategists, sales staff and other analysts, may take views that are inconsistent with those
taken in this research report. Deutsche Bank issues a variety of research products, including fundamental analysis,
equity-linked analysis, quantitative analysis and trade ideas. Recommendations contained in one type of communication
may differ from recommendations contained in others, whether as a result of differing time horizons, methodologies or
otherwise. Deutsche Bank and/or its affiliates may also be holding debt securities of the issuers it writes on.
Analysts are paid in part based on the profitability of Deutsche Bank AG and its affiliates, which includes investment
banking revenues.
Opinions, estimates and projections constitute the current judgment of the author as of the date of this report. They do
not necessarily reflect the opinions of Deutsche Bank and are subject to change without notice. Deutsche Bank has no
obligation to update, modify or amend this report or to otherwise notify a recipient thereof if any opinion, forecast or
estimate contained herein changes or subsequently becomes inaccurate. This report is provided for informational
purposes only. It is not an offer or a solicitation of an offer to buy or sell any financial instruments or to participate in any
particular trading strategy. Target prices are inherently imprecise and a product of the analyst’s judgment. The financial
instruments discussed in this report may not be suitable for all investors and investors must make their own informed
investment decisions. Prices and availability of financial instruments are subject to change without notice and
investment transactions can lead to losses as a result of price fluctuations and other factors. If a financial instrument is
denominated in a currency other than an investor's currency, a change in exchange rates may adversely affect the
investment. Past performance is not necessarily indicative of future results. Unless otherwise indicated, prices are
current as of the end of the previous trading session, and are sourced from local exchanges via Reuters, Bloomberg and
other vendors. Data is sourced from Deutsche Bank, subject companies, and in some cases, other parties.
Macroeconomic fluctuations often account for most of the risks associated with exposures to instruments that promise
to pay fixed or variable interest rates. For an investor who is long fixed rate instruments (thus receiving these cash
flows), increases in interest rates naturally lift the discount factors applied to the expected cash flows and thus cause a
loss. The longer the maturity of a certain cash flow and the higher the move in the discount factor, the higher will be the
loss. Upside surprises in inflation, fiscal funding needs, and FX depreciation rates are among the most common adverse
macroeconomic shocks to receivers. But counterparty exposure, issuer creditworthiness, client segmentation, regulation
(including changes in assets holding limits for different types of investors), changes in tax policies, currency
convertibility (which may constrain currency conversion, repatriation of profits and/or the liquidation of positions), and
settlement issues related to local clearing houses are also important risk factors to be considered. The sensitivity of fixed
income instruments to macroeconomic shocks may be mitigated by indexing the contracted cash flows to inflation, to
FX depreciation, or to specified interest rates – these are common in emerging markets. It is important to note that the
index fixings may -- by construction -- lag or mis-measure the actual move in the underlying variables they are intended
to track. The choice of the proper fixing (or metric) is particularly important in swaps markets, where floating coupon
rates (i.e., coupons indexed to a typically short-dated interest rate reference index) are exchanged for fixed coupons. It is
also important to acknowledge that funding in a currency that differs from the currency in which coupons are
denominated carries FX risk. Naturally, options on swaps (swaptions) also bear the risks typical to options in addition to
the risks related to rates movements.
11 April 2016
Annual Default Study: Past the Point of No Return?
Page 48 Deutsche Bank AG/London
Derivative transactions involve numerous risks including, among others, market, counterparty default and illiquidity risk.
The appropriateness or otherwise of these products for use by investors is dependent on the investors' own
circumstances including their tax position, their regulatory environment and the nature of their other assets and
liabilities, and as such, investors should take expert legal and financial advice before entering into any transaction similar
to or inspired by the contents of this publication. The risk of loss in futures trading and options, foreign or domestic, can
be substantial. As a result of the high degree of leverage obtainable in futures and options trading, losses may be
incurred that are greater than the amount of funds initially deposited. Trading in options involves risk and is not suitable
for all investors. Prior to buying or selling an option investors must review the "Characteristics and Risks of Standardized
Options”, at http://www.optionsclearing.com/about/publications/character-risks.jsp. If you are unable to access the
website please contact your Deutsche Bank representative for a copy of this important document.
Participants in foreign exchange transactions may incur risks arising from several factors, including the following: ( i)
exchange rates can be volatile and are subject to large fluctuations; ( ii) the value of currencies may be affected by
numerous market factors, including world and national economic, political and regulatory events, events in equity and
debt markets and changes in interest rates; and (iii) currencies may be subject to devaluation or government imposed
exchange controls which could affect the value of the currency. Investors in securities such as ADRs, whose values are
affected by the currency of an underlying security, effectively assume currency risk.
Unless governing law provides otherwise, all transactions should be executed through the Deutsche Bank entity in the
investor's home jurisdiction.
United States: Approved and/or distributed by Deutsche Bank Securities Incorporated, a member of FINRA, NFA and
SIPC. Analysts employed by non-US affiliates may not be associated persons of Deutsche Bank Securities Incorporated
and therefore not subject to FINRA regulations concerning communications with subject companies, public appearances
and securities held by analysts.
Germany: Approved and/or distributed by Deutsche Bank AG, a joint stock corporation with limited liability incorporated
in the Federal Republic of Germany with its principal office in Frankfurt am Main. Deutsche Bank AG is authorized under
German Banking Law and is subject to supervision by the European Central Bank and by BaFin, Germany’s Federal
Financial Supervisory Authority.
United Kingdom: Approved and/or distributed by Deutsche Bank AG acting through its London Branch at Winchester
House, 1 Great Winchester Street, London EC2N 2DB. Deutsche Bank AG in the United Kingdom is authorised by the
Prudential Regulation Authority and is subject to limited regulation by the Prudential Regulation Authority and Financial
Conduct Authority. Details about the extent of our authorisation and regulation are available on request.
Hong Kong: Distributed by Deutsche Bank AG, Hong Kong Branch.
India: Prepared by Deutsche Equities India Pvt Ltd, which is registered by the Securities and Exchange Board of India
(SEBI) as a stock broker. Research Analyst SEBI Registration Number is INH000001741. DEIPL may have received
administrative warnings from the SEBI for breaches of Indian regulations.
Japan: Approved and/or distributed by Deutsche Securities Inc.(DSI). Registration number - Registered as a financial
instruments dealer by the Head of the Kanto Local Finance Bureau (Kinsho) No. 117. Member of associations: JSDA,
Type II Financial Instruments Firms Association and The Financial Futures Association of Japan. Commissions and risks
involved in stock transactions - for stock transactions, we charge stock commissions and consumption tax by
multiplying the transaction amount by the commission rate agreed with each customer. Stock transactions can lead to
losses as a result of share price fluctuations and other factors. Transactions in foreign stocks can lead to additional
losses stemming from foreign exchange fluctuations. We may also charge commissions and fees for certain categories
of investment advice, products and services. Recommended investment strategies, products and services carry the risk
of losses to principal and other losses as a result of changes in market and/or economic trends, and/or fluctuations in
market value. Before deciding on the purchase of financial products and/or services, customers should carefully read the
relevant disclosures, prospectuses and other documentation. "Moody's", "Standard & Poor's", and "Fitch" mentioned in
this report are not registered credit rating agencies in Japan unless Japan or "Nippon" is specifically designated in the
name of the entity. Reports on Japanese listed companies not written by analysts of DSI are written by Deutsche Bank
11 April 2016
Annual Default Study: Past the Point of No Return?
Deutsche Bank AG/London Page 49
Group's analysts with the coverage companies specified by DSI. Some of the foreign securities stated on this report are
not disclosed according to the Financial Instruments and Exchange Law of Japan.
Korea: Distributed by Deutsche Securities Korea Co.
South Africa: Deutsche Bank AG Johannesburg is incorporated in the Federal Republic of Germany (Branch Register
Number in South Africa: 1998/003298/10).
Singapore: by Deutsche Bank AG, Singapore Branch or Deutsche Securities Asia Limited, Singapore Branch (One Raffles
Quay #18-00 South Tower Singapore 048583, +65 6423 8001), which may be contacted in respect of any matters
arising from, or in connection with, this report. Where this report is issued or promulgated in Singapore to a person who
is not an accredited investor, expert investor or institutional investor (as defined in the applicable Singapore laws and
regulations), they accept legal responsibility to such person for its contents.
Taiwan: Information on securities/investments that trade in Taiwan is for your reference only. Readers should
independently evaluate investment risks and are solely responsible for their investment decisions. Deutsche Bank
research may not be distributed to the Taiwan public media or quoted or used by the Taiwan public media without
written consent. Information on securities/instruments that do not trade in Taiwan is for informational purposes only and
is not to be construed as a recommendation to trade in such securities/instruments. Deutsche Securities Asia Limited,
Taipei Branch may not execute transactions for clients in these securities/instruments.
Qatar: Deutsche Bank AG in the Qatar Financial Centre (registered no. 00032) is regulated by the Qatar Financial Centre
Regulatory Authority. Deutsche Bank AG - QFC Branch may only undertake the financial services activities that fall
within the scope of its existing QFCRA license. Principal place of business in the QFC: Qatar Financial Centre, Tower,
West Bay, Level 5, PO Box 14928, Doha, Qatar. This information has been distributed by Deutsche Bank AG. Related
financial products or services are only available to Business Customers, as defined by the Qatar Financial Centre
Regulatory Authority.
Russia: This information, interpretation and opinions submitted herein are not in the context of, and do not constitute,
any appraisal or evaluation activity requiring a license in the Russian Federation.
Kingdom of Saudi Arabia: Deutsche Securities Saudi Arabia LLC Company, (registered no. 07073-37) is regulated by the
Capital Market Authority. Deutsche Securities Saudi Arabia may only undertake the financial services activities that fall
within the scope of its existing CMA license. Principal place of business in Saudi Arabia: King Fahad Road, Al Olaya
District, P.O. Box 301809, Faisaliah Tower - 17th Floor, 11372 Riyadh, Saudi Arabia.
United Arab Emirates: Deutsche Bank AG in the Dubai International Financial Centre (registered no. 00045) is regulated
by the Dubai Financial Services Authority. Deutsche Bank AG - DIFC Branch may only undertake the financial services
activities that fall within the scope of its existing DFSA license. Principal place of business in the DIFC: Dubai
International Financial Centre, The Gate Village, Building 5, PO Box 504902, Dubai, U.A.E. This information has been
distributed by Deutsche Bank AG. Related financial products or services are only available to Professional Clients, as
defined by the Dubai Financial Services Authority.
Australia: Retail clients should obtain a copy of a Product Disclosure Statement (PDS) relating to any financial product
referred to in this report and consider the PDS before making any decision about whether to acquire the product. Please
refer to Australian specific research disclosures and related information at
https://australia.db.com/australia/content/research-information.html
Australia and New Zealand: This research, and any access to it, is intended only for "wholesale clients" within the
meaning of the Australian Corporations Act and New Zealand Financial Advisors Act respectively.
Additional information relative to securities, other financial products or issuers discussed in this report is available upon
request. This report may not be reproduced, distributed or published without Deutsche Bank's prior written consent.
Copyright © 2016 Deutsche Bank AG
David Folkerts-Landau Chief Economist and Global Head of Research
Raj Hindocha Global Chief Operating Officer
Research
Marcel Cassard Global Head
FICC Research & Global Macro Economics
Steve Pollard Global Head
Equity Research
Michael Spencer Regional Head
Asia Pacific Research
Ralf Hoffmann Regional Head
Deutsche Bank Research, Germany
Andreas Neubauer Regional Head
Equity Research, Germany
International Locations
Deutsche Bank AG
Deutsche Bank Place
Level 16
Corner of Hunter & Phillip Streets
Sydney, NSW 2000
Australia
Tel: (61) 2 8258 1234
Deutsche Bank AG
Große Gallusstraße 10-14
60272 Frankfurt am Main
Germany
Tel: (49) 69 910 00
Deutsche Bank AG
Filiale Hongkong
International Commerce Centre,
1 Austin Road West,Kowloon,
Hong Kong
Tel: (852) 2203 8888
Deutsche Securities Inc.
2-11-1 Nagatacho
Sanno Park Tower
Chiyoda-ku, Tokyo 100-6171
Japan
Tel: (81) 3 5156 6770
Deutsche Bank AG London
1 Great Winchester Street
London EC2N 2EQ
United Kingdom
Tel: (44) 20 7545 8000
Deutsche Bank Securities Inc.
60 Wall Street
New York, NY 10005
United States of America
Tel: (1) 212 250 2500
