Description
The study examines the roles of capital rules, macro variables and bank business models
in determining the safety of banks as measured by the “distance-to-default” (DTD) with the purpose of
drawing implications for regulation of bank capital and business models
Journal of Financial Economic Policy
Bank business models, capital rules and structural separation policies: An evidence-
based critique of current policy trends
Adrian Blundell-Wignall Caroline Roulet
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Adrian Blundell-Wignall Caroline Roulet , (2013),"Bank business models, capital rules and structural
separation policies", J ournal of Financial Economic Policy, Vol. 5 Iss 4 pp. 339 - 360
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Paul Cavelaars, J oost Passenier, (2012),"Follow the money: What does the literature on banking tell
prudential supervisors about bank business models?", J ournal of Financial Regulation and Compliance,
Vol. 20 Iss 4 pp. 402-416http://dx.doi.org/10.1108/13581981211279354
J acopo Carmassi, Richard J ohn Herring, (2013),"Living wills and cross-border resolution of systemically
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Bank business models,
capital rules and structural
separation policies
An evidence-based critique
of current policy trends
Adrian Blundell-Wignall and Caroline Roulet
OECD, Paris, France
Abstract
Purpose – The study examines the roles of capital rules, macro variables and bank business models
in determining the safety of banks as measured by the “distance-to-default” (DTD) with the purpose of
drawing implications for regulation of bank capital and business models.
Design/methodology/approach – Apanel regressionstudyusingpre- andpost-crisis datafor 108US
and European banks is used to explore the issue empirically. Anewtechnique is also used to back out the
amount of capital banks would have needed during the crisis to keep the “DTD” in the very safe zone.
Findings – The simple leverage ratio has a strong relationship with “DTD”, while the Basel ratio
does not. The most important business model features are derivatives and wholesale funding, which
have a strong negative relationship with “DTD”. Trading and available-for-sale securities have a
positive in?uence. Calculations show that it is not possible for any reasonable capital rule to
compensate for the risks created by business model features encompassing large derivative-based
activities. Bank separation policies are essential.
Originality/value – The micro evidence-based analysis as an approach to bank regulation and
business model requirements stands in contrast to the ad hoc way policy has been constructed before
and after the crisis. The empirical evidence supports separation based on the balance sheet size of
derivatives and a leverage ratio instead of the complex Basel risk-weighted capital approach. The
current approaches to structural separation are criticised constructively, and some evidence-based
suggestions for improving bank business models to reduce systemic risk are made.
Keywords Derivatives, Bankbusiness models, Deleveraging, Distance-to-default, Structural separation,
Banking reform, GSIFI banks
Paper type Research paper
1. Introduction
The reasons given for the global ?nancial crisis include too much deregulation, poor
regulation, and ?nancial innovations that led to new trends in structured products and
securitisations involving derivatives and counterparty risks. Securities businesses
expanded rapidly relative to traditional banking based mainly on deposit taking and
lending. Traditional bank lending was based on private information created by the due
diligence of banks, whereas securities businesses operate through capital markets,
The current issue and full text archive of this journal is available at
www.emeraldinsight.com/1757-6385.htm
JEL classi?cation – G01, G15, G18, G20, G21, G24, G28
The views in this paper are those of the authors and do not necessarily re?ect those of any
member government of the OECD. The authors are grateful to Paul Atkinson for comments on
an earlier draft.
Journal of Financial Economic Policy
Vol. 5 No. 4, 2013
pp. 339-360
qEmerald Group Publishing Limited
1757-6385
DOI 10.1108/JFEP-06-2013-0025
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credit ratings and a labyrinth of complex underlying counterparty relationships. Some
of the innovations, where end-users are concerned, were socially useful, but many
others were related to new possibilities for tax and regulatory arbitrage that took the
size of the banking sector and its share of corporate pro?ts to unprecedented levels.
The combined effect of these measures was to undermine effective capital
requirements and to permit an explosion of leverage and interconnectedness within
the ?nancial system that ultimately collapsed upon itself.
The aftermath has seen the ?nancial crisis cause recession and unemployment on a
scale not seen since the great depression, a ?asco that would have been much worse were
it not for the emergency actions of central banks and some treasury authorities in
massive support policies that have no historical benchmarks with which to compare and
assess their long-run effects. These macro cyclical policies are not suitable for
addressing the structural factors that led to the crisis – they were supposed to be
temporary proceeding hand-in-hand with regulatory reform. Unfortunately, the banks
have been successful in pushing back on the two main directions of that reform process:
the needs to raise capital requirements of banks and to reverse the trend in
interconnectedness via the structural separation of bank business models. The banks
favour the Basel risk-weighting approach, which is ineffective, and ?ght hard to exempt
fromseparation the business activities that matter the most. This debate on the needs for
reform has not been informed by empirical research on capital rules that might work to
constrain leverage. Nor has there been evidence to suggest whether business model risk
can be compensated for by capital rules. If some business model features have a large
and independent in?uence on default risk, such that practical capital rules to offset them
are not feasible, then structural separation policies are unavoidable. If so, it is important
to know which business model features are most critical and which are not. The reform
process so far has focused on reforming Basel II into Basel III, and the attempts at
structural separation have taken very different paths (none of which are based on hard
empirical evidence) in the various jurisdictions. The latter include the Dodd-Frank
Volcker rule for the USA, the Vickers review for the UK and the Liikanen group report
for Europe. Switzerland has already adopted a different approach to all of these, and
within Europe countries are already diverging from what Liikanen proposed.
This paper follows up an earlier study by the OECD which was the ?rst to provide
hard empirical evidence on the above issues concerning capital rules and the structural
business model features that drive the default path (Blundell-Wignall and Roulet, 2012).
Section 2 introduces the distance-to-default (DTD) measure, which is the key analytical
tool used to analyse the largest banks in the USA and Europe. The asset-weighted time
series for the DTD is shown, as is the position of US versus European banks in the most
recent year 2012. The empirical evidence presented in Section 3 con?rms the results from
the earlier study. These show that the simple leverage ratio has a strong relationship
with the DTD, while the Basel ratio does not. The main business model features that
matter are derivatives and wholesale funding, which have a strong negative relationship
with the DTD. Trading and available for sale securities on the other hand, because they
enhance liquidity in the face of margin and collateral calls, has a positive relationship
with the DTD. This ?nding is particularly problematic for the recommendations of the
Liikanen group. Anewempirical ?nding is presented in Section 3, which shows that it is
simply not possible for a rational capital rule to compensate for the risks created by
business model features. Section 4 explains how complexity and interdependence
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operates in banks that combine securities businesses (particularly derivatives) with
more traditional banking – it provides examples that illustrate just why the hard
empirical evidence points to derivatives and wholesale funding as the main problem
areas in modern banking. In Section 5, current approaches to structural separation are
criticised constructively. Finally, evidence-based suggestions for separation with the
objective of improving bank business models and, thereby, to reduce systemic risk, are
made in the concluding Section 6.
2. Solvency: the DTD
The DTD is a measure that uses a combination of bank reported data, and market
information to calculate the number of standard deviations a bank is from the default
point, where the market values of assets equals the book value of debt. The formula to
calculate the DTD is derived from the option-pricing model of Black and Scholes (1973)
and is set out as follows:
DTD
t
¼
logðV
t
=D
t
Þ þðr
f
2ðs
2
t
=2ÞÞ · T
s
t
????
T
p ð1Þ
where:
V
t
market value of bank’s asset at time t.
r
f
risk-free interest rate.
D
t
book value of the debt at time t.
s
t
volatility of bank’s asset at time t.
T maturity of the debt.
The calculation is set out in more detail in the Appendix.
Figure 1 shows a time series of the asset-weighted daily DTD calculations of
69 banks, including GSIFI banks, alongside the average quarterly ROE’s, for those in
Europe, the UK and the USA[1].
From 1997 to 2004 the DTD typically averaged three standard deviations. For the
large GSIFI banks, innovations through capital markets securitisation of loans and the
huge demand for structured products to arbitrage the tax system made possible large
hitherto unexploited pro?t opportunities – ROE’s rose sharply from 2002 to 2007[2],
as did the DTD. The main policymaker thinking at this time favoured deregulation for
better ef?ciency and growth, while banks took advantage of this to minimise capital
costs and raise their ROE’s. The DTD, being based on market data gives a more
reliable picture of the likely solvency and liquidity problems of a bank than do ROE’s.
The weighted average DTD fell to 0 in the UK and the USA, implying systemic
insolvency, with many individual banks below the zero point. The DTD fell to below
1 in Europe, with many banks below the solvency point. The USA has recovered more
quickly in 2011-2012, while many European banks are still not at a safe point.
The DTD for individual banks for the most recent year 2012 is shown in Figure 2 for
the same 69 largest US and European banks (the UK and Switzerland are shown with
Europe). It is very clear that the US response to the crisis, with forced capital injections
Bank business
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Figure 1.
Average DTD and
bank ROE’s
–10
–5
0
5
10
15
20
25
0
1
2
3
4
5
6
7
8
9 %
Std Dev.
USA
Weighted DTD ( LHS) Weighted ROE
–15
–10
–5
0
5
10
15
20
0
1
2
3
4
5
6
7
% Std Dev.
Europe
Weighted DTD (LHS) Weighted ROE
–25
–20
–15
–10
–5
0
5
10
15
20
25
0
1
2
3
4
5
6
7
8
D
e
c
-
9
7
A
u
g
-
9
8
A
p
r
-
9
9
D
e
c
-
9
9
A
u
g
-
0
0
A
p
r
-
0
1
D
e
c
-
0
1
A
u
g
-
0
2
A
p
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-
0
3
D
e
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-
0
3
A
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0
4
A
p
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-
0
5
D
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-
0
5
A
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-
0
6
A
p
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-
0
7
D
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-
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7
A
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8
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-
1
2
A
p
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-
1
3
D
e
c
-
1
3
%
Std Dev.
United Kingdom
Weighted DTD (LHS) Weighted ROE
Source: OECD, Bloomberg
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following proper stress tests on bank assets has led to US banks moving back above
the safe zone of three standard deviations[3].
3. Capital rules versus bank separation
Many European banks and a few US banks need more capital and/or structural
reforms to promote a safer banking system. But the issue that continues to perplex
policy making concerns the right balance between capital rules and business model
reform – where the latter includes the Vickers recommendations
(Blundell-Wignall et al., 2009; Independent Commission on Banking, 2011); the
Dodd-Frank Act Volcker rule[4]; and the Liikanen proposal that is in?uencing
decisions in a number of European countries including France and Germany (Liikanen,
2012). What capital rule works best? Are capital rules enough? And if separation is
important, what is the best way to implement it?
Most international organisations other than the OECD tend to favour improving the
existing system of bank regulation and capital rules, while adding the desire for
“credible” bank resolution regimes to address the too-big-too-fail (TBTF) problem of
the cross-subsidisation of risk. The BCBS and the FSB have focused on replacing Basel
II with Basel III and improved cross-border cooperation. This approach is supported by
IMF studies that argue that the best approach to improve bank safety is:
[. . .] (i) more stringent capital (and possibly liquidity) requirements to limit contribution to
systemic risk; (ii) intensive supervision consistent with the complexity and riskiness of SIFIs;
(iii) enhanced transparency and disclosure requirements to capture emerging risks in the
broader ?nancial system; and (iv) effective resolution regimes at the national and global level
to make orderly resolution a credible option, with resolution plans and tools that lead
creditors to share any losses (O
¨
tker-Robe, 2011, p. 2).
Academics have stressed the dif?culties of interpreting rules based on separation
proposals, and some have been strongly against it[5]. Much of this discussion is based
on literature that predates the crisis, casual empiricism and theoretical argumentation.
But so far the various proposals have not been informed by and based on empirical
Figure 2.
DTD in 2012: the USA
versus Europe
7
6
Std Dev.
US banks European banks
Source: OECD, Bloomberg
5
4
3
2
1
0
1 3 5 7 9 11 13 15 17 19 21 2 4 6 8 10 12 14 16 18 20 22 24 26 28 30 32 34 36 38 40 42 44 46
–1
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research as to what determines sudden moves towards the default point. Nor has there
been any convincing evidence on the type of capital rule that would be enough to make
banks safe.
3.A. Simple capital rules help but independent business-model effects are too powerful
A panel regression approach is used to explain the differences in DTD’s across banks
over the period 2004-2012. The sample consists of the top 100 US and EUinternationally
active commercial banks andbroker-dealers byequitymarket capitalisation. Inaddition,
six banks that failed in the crisis, but which can be considered as GSIFI’s, HBOS,
Merrill Lynch, Lehman Brothers, Washington Mutual, Wachovia and Bear Stearns are
included. There are a total of 108 banks in the sample, consisting of 21 FSB GSIFI banks
(excluding Asian and non-listed banks), six failed former GSIFI banks, two banks with a
system-wide importance in their related countries (i.e., Intesa San Paolo and Banco
Bilbao Vizcaya Argentaria)[6] and 79 other large banks. Only publicly traded banks are
included, because market data are required for the model. The data includes all of the
banks that carry out the counterparty activities in derivatives and other securities that
are a key focus of this study.
The empirical model takes account of the TBTF incentive for excessive risk taking,
macro-prudential in?uences, leverage, and business model aspects. The equation is
estimated with two alternatives for leverage: the leverage ratio and the regulatory
capital approach of the Basel Tier 1 ratio. The empirical model is speci?ed in
equation (1); where the subscripts i and t denote the bank and the period, respectively:
DTD
i;t
¼ /
i;t
þb
1
TA
i;t
þb
2
K
i;t
þb
3
TD
i;t
þb
4
WFD
i;t
þb
5
GMV
i;t
þb
7
BETA
i;t
þb
8
%HPI
i;t
ð2Þ
TA is size variable relating to the TBTF issue, equal to the total assets of the bank as a
share of total assets in the national banking system. It is expected to be inversely related
to the DTD. K corresponds to the simple rule leverage ratio (LEV), which is expected to
have a negative sign, or to the Basel Tier 1 ratio (T1), which is expected to have a positive
sign. The equation is estimated twice, once with LEV, excluding the Basel capital
concept, and once with T1, excluding the simple leverage ratio. TD is the sum of the
trading book and available-for-sale securities, and is expected to have a positive sign.
The reason for this is that liquidity drives the banks’ path to default in practice, when
margin and collateral calls cannot be delivered. Liquid assets can be sold or used as
collateral. WFD refers to wholesale funding as a share of total liabilities and is expected
to have a negative sign – higher wholesale funding typically at a shorter duration is less
stable than deposits for funding longer term assets. GMV refers to the gross market
value of derivatives as a share of the banks’ total assets – appropriately converting all
USbanks to the IFRSconcept for consistency. GMVis expectedto have a negative sign –
this is the quintessential interconnectedness variable where volatility drives rapid
changes in margin requirements. BETA is a macro control variable, de?ned as the
covariance of the ?rm’s stock price with the national stock market, using daily data to
calculate annual observations, divided by the variance of the national stock index.
It is expected to have a negative sign, on the grounds that the ?rm is more connected to
the national macro and asset price cycle. Finally, %HPI refers to the annual percentage
change in the national house price index, and is expected to have a positive sign on
the grounds that rising prices improve a borrower’s equity in the home and vice versa.
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The two equations for the LEVand T1 alternatives are estimated for all banks, the GSIFI
banks and the other large banks in the sample, using ordinary least squares (OLS). After
testing for cross-section versus time-?xed versus random effects, and for the
heteroskedasticity of error, cross-section and time-?xed effects are introduced into the
regression. The regression results are shown in Table I[7].
The simple leverage ratio argument is well determined at the 1 per cent level, for all
banks, the GSIFI banks and the other large bank panels, but the Basel Tier 1 ratio
appears to ?nd no support as a determinant of the DTD in any model. Focusing on the
?rst (LEV) equation the macro control variables in house prices and the market beta are
correctly signed and signi?cant at the 1 per cent level, across all models. With respect to
in?uences on risk taking, the results show that the size of a bank in its own market
(TBTF) is signi?cant at the 1 per cent level for all banks and in the other large
bank samples, but not for the small sample of GSIFI banks only. The reason for this
appears to be that all GSIFI banks are large, and there is less size diversity compared
All banks G-SIFIs banks Other large banks
Constant, a 9.17
* * *
8.26
* * *
11.66
* * *
11.46
* * *
8.52
* * *
7.46
* * *
(18.21) (13.12) (9.02) (8.62) (16.19) (10.48)
TA: bank TA/ntl.
bank assets
23.30
* * *
23.88
* * *
21.70 22.36 26.70
* * *
26.63
* * *
(22.62) (22.74) (21.08) (21.30) (22.92) (22.54)
LEV: TA/bank
equity
20.04
* * *
– 20.03
* * *
– 20.06
* * *
–
(22.97) (22.51) (22.81)
T1: Basel Tier 1
ratio
– 21.31 – 1.24 – 1.57
(0.57) (0.24) (1.14)
TD: trading book
plus available for
sale securities/TA
2.36
* *
1.94
*
3.94
* *
3.73
* *
1.15 0.52
(2.27) (1.79) (2.04) (1.96) (0.97) (0.37)
WFD: wholesale
funding/total
liabilities
22.43
* * *
21.39
* *
26.08
* * *
25.49
* * *
21.70 20.72
(22.78) (21.69) (23.75) (23.29) (21.54) (20.57)
GMV: GMV of
derivatives/TA
25.22
* * *
28.22
* * *
26.16
* * *
28.47
* * *
21.67 25.33
(23.99) (25.73) (23.72) (24.61) (20.67) (21.59)
BETA: CoVar bank
stock ret. with ntl.
mkt ret./var. mkt
22.36
* * *
22.73
* * *
22.80
* * *
23.54
* * *
22.16
* * *
22.05
* * *
(212.26) (212.48) (210.51) (211.49) (29.21) (28.73)
%HPI: House Price
Index ann. %
change
13.18
* * *
16.81
* * *
14.30
* * *
16.58
* * *
13.37
* * *
13.91
* * *
(11.50) (16.12) (8.13) (8.90) (8.96) (10.20)
R
2
0.74 0.72 0.79 0.77 0.72 0.72
Fisher statistic 16.75 14.98 20.30 17.78 14.27 14.15
p-value F 0.00 0.00 0.00 0.00 0.00 0.00
Total observations 728 690 223 205 505 485
Notes: Statistical signi?cant at:
*
10,
* *
5 and
* * *
1 per cent levels; this table shows the results of
estimating multi-variate regressions for an unbalanced panel of 108 US and European internationally
active commercial banks and broker dealers with equity market capitalization in excess of $5bn over
the period 2004-2012; cross-section and time ?xed effects are used in the regressions as is the White
diagonal covariance method
Source: OECD
Table I.
Determinants of bank
DTD: multi-variate
panel results
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6
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to the larger samples. In terms or arguments relating to the business model, the GMV of
derivatives and wholesale funding have the expected negative signs and are signi?cant
at the 1 per cent level for the full sample and for the GSIFI group, but not for the other
large banks (which have only a small derivatives component in their portfolios). Trading
assets have the expected positive signs that ?nd support at the 5 per cent level for the full
sample and the GSIFI banks, but not in a sample that excludes the GSIFI’s.
The evidence suggests that a simple leverage ratio strongly outperforms the complex
risk-weighting approach of the Basel Tier 1 ratio. With regard to business model factors,
the evidence suggests that derivatives and wholesale funding are powerful in?uences on
the DTD which are quite independent of the leverage ratio. These factors appear to be
related mainly to the activities of the GSIFI banks in the sample. These risks can
be ameliorated by the holding of liquid trading securities, which provide liquidity in the
face of margin and collateral calls. However, wrong-way risk in a bout of volatility can
lead to increased margin calls and falling collateral values, in which case the ability to
borrow to fund the gap in the wholesale market is even more critical.
3.B. Explaining why the simple leverage ratio works and why the Basel ratio does not
The Basel Tier 1 ratio applies to risk-weighted assets (RWA), and banks use RWA as a
management tool toreduce the cost of equity, i.e. theyoperate toreduce the ratioof RWAto
TA, enabling leverage to rise even as regulators try to ensure banks have stronger capital
buffers. Under the Basel system total RWA are de?ned (for an 8 per cent Tier 1 ratio) as:
RWA ¼ 12:5 ðOR þMRÞ þ
X
n
i¼1
ðw
i
ÞA
i
ð3Þ
where OR is operational risk, MR is market risk, both of which are grossed up by 12.5 for
8 per cent equivalence, w is an asset risk weight, and A is an asset. This Basel II
representation has been re?ned and added to in Basel III reforms: to raise the quality of
capital; to add buffers for large banks and to add charges for counterparty credit risk (CCR).
By2018banks wouldbe expectedtohave 4.5per cent of RWAas core Tier 1 (close to equity),
and additional equity buffer of 2.5 per cent, adding to 7 per cent (for core Tier 1 plus buffer).
The Tier 1 ratio is set at a 6 per cent minimum. But these reforms do not address
the fundamental criticisms levelled by the OECD on frequent occasions since 2008
(Gordy, 2003):
.
The framework is mathematically based on a single global risk factor for all
banks regardless of their situation – it ignores idiosyncratic risk.
.
The portfolio invariance principle, that risk attributes of any asset are speci?c to
the asset and hence the additivity principle can apply – and hence there is no
Tier 1 penalisation of the concentration of assets.
.
It continues to allow banks to use their own models to estimate VaR’s, their risk
weights and illiquid asset prices (mark to model).
.
Banks can continue to shift the ownership of assets and transform the measured
riskiness of assets via derivatives and SPV’s in the shadow banking system.
.
It does not and cannot deal (see below) with counterparty risk and derivatives.
The Basel rules also permitted banks to use broad concepts of capital to satisfy the
numerator of the Tier 1 ratio (including subordinated debt, hybrids, etc.), instead of
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(costly) pure equity, with each jurisdiction allowing different rules. The announcement of
Basel II in July 2004 (to have been implemented by 2008), and the SEC’s removal of
leverage controls on investment banks, actually encouraged the rapid growth in leverage
and the pro?tability of banks[8]. Figure 3 shows the asset-weighted ratio RWA to total
assets (TA) for 27 GSIFI banks (i.e. 21 GSIFI banks de?ned by the FSB and six former
GSIFI banks that failed in the crisis referred to earlier), and 564 non-GSIFI banks. The use
of models and hedging to lower the ratio of RWA/TA is systematic – banks risk-weight
optimise to minimise the cost of capital and to improve returns for shareholders[9].
Many policy makers at international organisations appear to believe that business
model reform is unnecessary, and that ?nancial stability can be handled by reform of
the capital rules combined with credible resolution mechanisms to deal with TBTF[10].
The problems with derivatives and repos that lead to margin collateral calls cannot be
handled by the Basel III reforms aimed at establishing more capital for banks and the
credit valuation adjustment (CVA) charge to deal with counterparty risk – the
amounts involved are just too large.
In Section 2 it was noted that a DTD minimum of three standard deviations, often
achieved in the late 1990s and early 2000s, is a reasonably safe level where there is only
a very small chance of default. What capital levels would have been enough to
guarantee this level of safety during the crisis period and more recently? To explore
this idea, the DTD model of equation (1) is ?rst solved – see the Appendix. DTD is then
set to 3.0 and (for a maturity of T ¼ 1) target bank capital K
*
is calculated by solving
for the V/D ratio that satis?es that condition for any bank below the critical 3.0
standard deviation threshold:
3:0:s
t
2 r
f
2
s
2
t
2
¼ log
V
t
D
t
¼ /
t
ð4Þ
Given that D ¼ TA 2 K, where TA is total assets, it is then possible to calculate K
*
holding s and V at their original solved values, given the historical observations of
TA:
Figure 3.
RWA to total assets:
GSIFI banks versus
non-GSIFI banks
R
2
= 84%
R
2
= 96%
25
30
35
40
45
50
55
60
65
70
75
2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012
%
G-SIFIs
Non G-SIFIs
Note: Business model risk factors for GSIFI banks cannot be dealt with by
capital rules
Source: OECD, Bloomberg
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t
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a
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The gap K
*
2 K is then computed is computed for each bank and summed over the
system[11]. This gap is calculated for 21 of the GSIFI banks in the USA and in Europe
(de?ned by the FSB, excluding Asian and non-listed banks) and for 48 other large
banks. It is also calculated for the USA, Europe and the UK data separately.
The results for all banks, the GSIFI banks and for the non-GSIFI banks are shown in
Figure 4. From 2002 to 2007 K
*
2 K is not material for most banks, underlining the
point that banks do not need capital, until they need it in a tail event. In 2008, an
additional $2.2tn was needed to keep all bank DTD levels at least at 3.0 standard
deviations, of which $1.6tn was required by the GSIFI banks and $600bn was required
by the other banks. In 2009, $4.5tn more capital was required, of which $3.6 was due to
the GSIFI banks. These amounts then fell away in 2010, and rose again to $600bn in
2011 ($450bn for GSIFI’s). Table II shows some of these amounts in ?gures and
provides a country breakdown. While the US capital needs were greater in 2008 and
2009 ($1.5tn and $2.5tn), Europe and the UK together were only a little less than these
amounts. In recent years the picture has changed substantially with the USA much
farther ahead in the capital raising and asset write-off process.
It is clear from this analysis that in a tail event GSIFI banks are very different to
other large banks. The DTD can rise sharply as margin and collateral calls rise with
volatility. In the worst two years of the crisis The GSIFI banks needed an average of
$2.1tn pa additional capital in 2008 and 2009 according to the DTD analysis. Figure 5
shows the actual changes in collateral demanded in those years for derivative
positions, according to ISDA. From December 2007 to December 2008, the estimated
collateral demanded rose from $2.1tn to $4tn, net rise in collateral demanded was
$1.8tn, and collateral demanded remained at $3.2tn in 2009. These numbers are
illustrative of the actual pressures that the banking system had to bear in the crisis
years relating to derivative margin calls related to trading and the structured product
businesses of mainly GSIFI banks. These were not the only pressures, as non-GSIFI
Figure 4.
The capital needs of banks
through the crisis period
0
500
1,000
1,500
2,000
2,500
3,000
3,500
4,000
4,500
5,000
1997 1998 1999 2000
Source: OECD, Bloomberg
2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012
$
U
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b
i
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All G-SIFIs Non G-SIFIs
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banks were also drawn into the securitisation and fee-for-sale business model, and the
large numbers seem broadly consistent with the ex ante measures calculated with
the DTD model. This analysis suggests that in a crisis there is no capital rule that will
be feasible before the event – these sums would have meant a capital rule that might
have tripled the capital held by banks prior to the crisis. For many individual GSIFI
banks tripling the capital would not have been suf?cient.
4. The interconnectedness problems with GSIFI banks
GSIFI banks do engage in consumer or retail banking, based on amortised cost
accounting, but their pro?t involvement in investment banking generally, and prime
broking, derivatives and structured product origination, market making and
underwriting, which are based on fair value through or loss (mark-to-market)
accounting, are complex and highly interconnected with other ?nancial institutions. All
of these activities involve inventories of products that are marked to market. In normal
$ billion
2007 2008 2009 2010 2011 2012
Type of bank
Global 13.7 2,225 4,560 363 616 314
G-SIFIs 7.2 1,624 3,611 250 449 203
Non G-SIFIs 6.5 602 949 113 166 111
Domicile of banks
USA 4.9 1,285 2,473 32 176 17
UK 3.2 252 1,075 79 80 53
Europe 5.6 689 1,013 252 359 245
Source: OECD, Bloomberg
Table II.
The capital needs of
banks and regional
breakdown
Figure 5.
The gross credit exposure
(GMV-netting) of
derivatives and collateral
0
1,000
Source: BIS, ISDA, OECD
2,000
3,000
4,000
5,000
6,000
M
a
r
-
0
0
S
e
p
-
0
0
M
a
r
-
0
1
S
e
p
-
0
1
M
a
r
-
0
2
S
e
p
-
0
2
M
a
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-
0
3
S
e
p
-
0
3
M
a
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4
S
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M
a
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5
S
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p
-
0
5
M
a
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-
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6
S
e
p
-
0
6
M
a
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-
0
7
S
e
p
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7
M
a
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0
8
S
e
p
-
0
8
M
a
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-
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9
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9
M
a
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1
0
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p
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M
a
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1
1
S
e
p
-
1
1
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a
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$
b
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Collateral
Gross Credit Exposure
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times risk management tools including netting of exposures, ?nancing through
tri-partite repos, and derivatives hedging work well and do not require much capital and
certainly not any of?cial support. Ina crisis, however, losses fromown activities, failures
of counterparties and the drying-up of liquidity can bring about insolvency that
reverberates through the ?nancial system.
Figure 6 shows some standard functions of such GSIFI banks. This simpli?ed
partial picture of just some of the securities market banking and ?nancing illustrates
just a few of the many issues that arise with counterparty risk.
The top section of Figure 6 shows a typical tri-partite repo transaction. A money
market fund (MMF) in the USA is essentially providing ?nance to a broker dealer in (say)
Europe (an af?liate of a universal bank). This ?nancing tool is interconnected with the
cash needs for the multiple activities of the broker dealer.
A failure of the broker dealer would put the clearing bank at risk with ?ow on effects to
other broker dealers ownedbybanks. These two clearingbanks like central clearingparties
for derivatives (discussedbelow) centralise riskandconnect multiple institutions. Typically
there is not a problem until there is a ?nancial event, in which case liquidity can suddenly
dryup[12]. The MMF(sayfromthe USA) maywithdrawfunds due to excessive exposure to
European banks when liquidity and solvency concerns arise. Concerns about losses in the
MMF could lead to a run on those funds, causing short-term funding to be withdrawn.
In a crisis situation pressure on the lender-of-last resort (LOLR) mechanism to ?ll
the liquidity gap becomes enormous. Injections of capital for the clearer and or the
investment banks in the repo market could be essential in extreme tail events, such as
occurred in 2009.
Figure 6.
Counterparty and
interconnectedness risk
Source: OECD, tri-partite repos
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4.A. Counterparty risk with OTC derivatives
In the middle section of Figure 6, the broker dealer (B-D) is engaging in derivative
transactions with two counterparties hedging its exposure. The overall system is
exposed to the tune of 270. Ignoring the case of the central clearing parties (CCP’s) for
the moment, consider the following examples:
.
There are no defaults, but the B-Dis down a net 20. The crucial point is that this net
20 margin has to be funded, for example, via a short-term repo loan. But in a crisis
situation, this might interact withthe problemof liquidity fromthe normal sources
drying up. The broker dealer cannot meet the margin call, and its parent (without a
?rewall) might try to support it, thereby contaminating other af?liates in the bank
or an insurance company dealing with banks. As AIG, Dexia and others found out,
this contamination can overwhelm the holding company in a crisis. There may be
no reasonable capital rule that could save the institution in a tail risk event.
.
One of the non-bank counterparties wants to unwind the trade during a risk
event (rather than post more collateral) and reset the contract at a higher safer
spread, losing some of its collateral in the process. But in the middle of a crisis
this may prove to be prohibitively expensive, and it may in fact be impossible to
enter a more attractive trade. It may fail, leaving the bank exposed and having to
fund a negative position;, e.g. the 100 owed to the ?rst counterparty.
4.B. Central clearing parties (CCP’s)
The middle of Figure 6 shows the alternative arrangement, provided the derivatives are
standardised, of clearing via a CCP. The regulatory authorities have put a lot of faith inthe
idea that clearing will solve many of the problems that arose in the crisis. Clearing
certainly makes for greater transparency, which is a good thing because it would work to
undermine excessive spreads in the OTC market by improving the scope for price
competition. But CCP’s do not somehow “destroy” risk. Like the clearing banks in a repo
transaction, the CCP needs capital, must model risk and set appropriate margins
commensurate with that risk. In the above trade, at the point in time shown, the net
exposure is 20 for the system, as opposed to gross exposures of 270. But the ability of the
CCP to guarantee the trades depends on its capital which should be suf?cient for all risk
scenarios. It is most important to understand that netting does not in any way mitigate
market risk. A bout of unexpected market volatility may turn the net 20 into something
much larger in a short space of time. The failure of a counterparty would be even more
problematic.
Much the same as a clearing bank in the tri-partite repo market, the CCP will require
sound risk management, and collateralisation via margin calls will need to be appropriate.
Clearing facilitates trading but the market risk remains. The under-pricing of that risk
and TBTF may be signi?cantly worse with a CCP. The CCP becomes a vital node,
interconnecting multiple players in the ?nancial system. The failure of such a node would
lead to multiple contamination effects compared to bilateral trading. In other words, the
problem of TBTF would likely be increased rather than reduced. The central bank and
the taxpayer could not allowthe CCP to fail. It is dif?cult to see howthis feature would not
lead to exactly the same under-pricing of risk that played such a large part in the crisis.
Indeed, competition between CCP’s can only really take the form of reducing collateral
requirements to make the cost of trading cheaper for counterparties, but the clear outcome
will be under-collateralisation and increased risk.
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Furthermore, there is the problem of what can and cannot be cleared. OTC interest
rate derivatives at over $500tn are a huge part of the derivatives market, and more than
half of the $246tn of interest rate swaps are cleared. These typically were not a source
of problem during the crisis. However, derivatives that cannot be cleared were in
the forefront of problems, and the non-cleared derivatives market includes most of
these:
.
Very long–term interest rate swaps (e.g. 15-19 years) sought after by pension
and insurance companies for liability management. A part of this market is
non-standard and cannot be cleared.
.
Single name credit default swaps (CDS), which were so prominent in the
AIG crisis, currently around $30tn. The CDS has the potential for extreme
collateral call shifts when the probability of the default of the reference entity
increases and if default actually occurs, the liability moves to the maximum.
.
Swaptions – options on interest rate swaps (the rights to swap ?xed and
variable interest rates). This is a large market of over $30tn, and is crucial in
managing long-term interest rate risk across many industries. For example, if
rates were thought to rise in the longer run, then a ?rm would have the option
(not obligation) by exercising a swaption to pay ?xed and receive the rising
?oating rate interest payments. These can be up to 30 years maturity and are
highly illiquid. They cannot be eligible for clearing. It was the inability to
manage the risks in this illiquid complex product that caused large losses
for Morgan-Stanley in its joint venture (MUFG) in Japan with Mitsubishi
securities.
.
Some parts of the forward rate agreement market for currencies cannot be
cleared – typically the longer the horizon the more illiquid the market.
.
Parts of the overnight index swap market cannot be cleared. The ?oating rate leg
is based on the reference rate of Fed funds or Libor, and it allows very short-term
borrowers to manage interest rate risk inherent in sudden changes in cost of
funding and income received on longer-term assets.
.
Many OTC commodity, energy and equity derivatives cannot be cleared.
Consider the following example. If a user takes a position in volatility with a swaption,
the trader will typically hedge the market risk in the position with an interest rate
option notional amount equal to some percentage of the swaption (the maturity and
coupon of the swap would mirror those of the swap on which the swaption is based).
But if the swap in mandated to be cleared with the CCP and the swaption is executed
bilaterally, there is no bene?t in clearing the swap from a risk point of view.
The greater complexity may raise risk and will certainly increase collateral costs
compared to keeping the swap and the swaption together bilaterally[13].
In short, there is some risk that clearing will apply to the derivatives which are
plain vanilla, and where risk is small to start with. Mandating CCP’s for low-risk
derivatives will improve transparency but also create a new the TBTF institution;
cause tensions between cleared and non-cleared derivatives to rise; and clearing will
not apply to the illiquid derivatives most likely to be the source of problems in a future
crisis.
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4.C. Supervisory and audit ability in the face of complexity
Finally, the bottom panel of Figure 6 shows an example related to alleged events in a
large GSIFI bank in recent years. The bank sold CDS protection to another
?nancial institution. The bank then hedged itself by buying a super senior tranche:
whereby an asset-backed commercial paper (ABCP) conduit posted collateral with the
bank in the form of a pool of reference assets, and the bank paid it a spread –
essentially the bank bought a put to hedge its CDS position. If the reference
pool of assets falls in value the ABCP conduit owes the bank money and tops up its
margin.
The alleged problem was one of complexity and the inability of the supervisor to
monitor what happened. The bank, before the tail event, did not really buy a put, but
instead bought a put spread with the idea of reducing the cost of protection. The losses
on the worst case scenario envisaged by the bank were, say, 15 per cent of the reference
pool. In such a case the bank could greatly reduce its cost of protection by basing the
premiums to be paid on the case of losses of up to the 15 per cent only. In the crisis,
however, a tail risk event emerged and the losses were much greater than the 15 per cent.
If true, the bank would not be covered, and by IFRS accounting rules the bank would
have to mark the losses to market. Instead, the bank may have accounted the position
based on a put and not the put spread, expecting the reference pool would recover in
value. The question is, can the supervisor and auditor, in practice, monitor at this level of
detail – look at all individual trade tickets and enforce the accounting rules.
Alternatively, there is the risk of regulatory forbearance: the regulator is informed but
works with the bank to avoid disruptive disclosures. Two scenarios are then possible:
(1) the asset pool recovers and whistle blower revelations fall on the deaf ears of the
involved authority; or
(2) the asset pool does not recover, and the bank risks major losses and possible
failure if it cannot fund the net position.
4.D. In summary: macro cyclical tools cannot solve structural issues
In all of these cases complexity and interdependence are the problem during a risk tail
event. There are so many players, and the pressure may come from any part of the
market and affect all the other parts. Liquidity can freeze up from a number of different
pressures and take down the ?nancial system in the absence of emergency policies.
Any of the counterparties may fail for a variety of reasons, or be unable to perform
their functions, resulting in margin calls not being funded. TBTF problems remain and
new one may be created with CCP’s. Forms of fraud and/or regulatory forbearance may
be present. Runs on deposits in MMF’s may be the driving point. Since the business
models of banks have not been fundamentally altered, the main lifting to deal with the
crisis has been cyclical liquidity policies. This in turn can lead to a new set of problems
by rekindling asset prices and leverage in securities markets, setting up for new
versions of the crisis later on. In short, the fundamental structural problem of business
model reform has not been dealt with. During the crisis, the contamination effect to
traditional banking functions of deposit taking and lending to consumers and small
and medium-sized businesses has been a prime causal factor in the recession and the
record unemployment in many jurisdictions.
Addressing the problems of ?awed bank business models and losses with cyclical
tools such as low interest rates, compressing the term premium, and emergency
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lending certainly helps banks but does not deal with the structural issues. If persisted
with for a long period, such policies will shift the bubble around to new sectors, such as
higher yielding corporate debt and to re?ate bank securities and structured products
back towards pre-crisis levels. If the response to the crisis is mainly cyclical and the
banks remain too large, too complex and too interconnected to fail, then risk will
continue to be under-priced, and little real reform will have been achieved. Figure 3
shows the asset-weighted balance sheets of banks in the USA, Europe and the UK.
5. The need for structural separation and current proposals
Banks argued successfully for the repeal of US separation policies that limited their
international business models. Just when European universal banks might have
bene?tted from the separation of traditional and investment banking, the regulatory
and business model trends were in exactly the opposite direction. The main drivers of
bank lobbying in this regard were the pro?tability of leverage, high OTC derivative
spreads, and the business model need to have suf?cient diversity of market views and
scale amongst derivative counterparties[14]. The above analysis shows that business
models have evolved to such a complex and interconnected state that there is no
reasonable capital rule that can be in place in normal times to protect the ?nancial
system in the event of major defaults and related bouts of market volatility.
The amounts of capital required to keep the DTD above three in a crisis are simply too
large. The panel regression results also showed that the DTD is sensitive only to the
simple leverage ratio and not the Basel ratio, while business model features have
strong independent effects on the DTD.
The Basel reforms for counterparty risk may be summarised as follows:
.
A CCR capital buffer based on expected exposures with a stress test of value at
risk in a market event that affects the probability of default of a counterparty –
which has the effect of raising RWA.
.
ACVA, which is an additional up-front charge to cover mark-to-market unexpected
counterparty losses (working through the MR term in the above equation 3). The
CVA is calculated by netting set, and is additive across netting sets.
.
In addition Basel is designed to encourage use of CCP’s and exchange traded
products, where reductions in capital cost can be achieved.
These Basel add-on proposals are subject to all the problems with modelling and moral
hazard noted earlier. But in addition to these, the CVA charge applies at the netting set
level, and is additive across netting sets. Like other aspects of Basel that have led to
problems in the past, the approach does not reward diversi?cation. A large number of
netting pools will give rise to less scope for cross-product netting, and more positive
and negative positions that will add to a positive CVA charge. If larger GSIFI banks
choose to deal more and more with each other, they increase the scope for cross-product
netting and reduce the CVA charge. Hence, the Basel rule encourages more
concentration in derivatives – it increases the TBTF problem in derivatives rather
than reducing it. Furthermore, netting is best suited to settlement process concepts –
netting provides no protection for market risk. Basing capital rules on netting pools –
encouraged by banks – is not in the interests of the future stability of the ?nancial
system. These rules will certainly not cause suf?cient capital to be held to compensate
for the absence of structural separation. As noted before, the panel regression results
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suggest that simple capital rules help, but they cannot compensate for the large impact
on the DTD of business model features. This brings the discussion back to the
necessity of structural separation and where the lines for separation should be drawn.
Indeed, the bank regulators paradox is that large complex and interconnected banks
need very little capital in the good times, but they can never have enough in an
extreme crisis. Separation is required to deal with this problem. The point of separation
is to avoid the cross-subsidisation from implicitly insured TBTF banks to securities
af?liates (of meaningful size) that engage in risking the banks own capital and liquidity
status in counterparty transactions with other institutions. These activities involve
derivatives and related products that require ready access to repo and other short-term
funding to meet margin and collateral calls which, in a crisis, may not be forthcoming for
all institutions; and hence the path to default (without of?cial support) can be
particularly rapid and spread between ?rms. Having such risk activities occur between
ring-fenced af?liates or separate ?rms that are not implicitly insured will be much less
serious, as market discipline will then ensure the correct pricing of risk through
appropriate segregations and margin requirement procedures. Supply and demand for
the activity will be commensurate with its underlying riskiness when the ability to
resolve the (smaller and separate) ?rm is credible in the eyes of all participants.
5.A. Volcker
The Volcker rule is complex and asks for rules to be written that depend on the intent
of a trader: servicing a client for a fee without speculating on short-term price
movements against which there is a blanket ban. Banks successfully argued that the
Volcker rule should continue to allow underwriting and market making, in spite of a
blanket ban on speculating on short-term price movements with the banks’ own
balance sheet – yet both of these activities involve banks taking inventory of assets,
the extent of which requires them to make a book and hedge speculations on future
price movements of that inventory. The banks have also succeeded in achieving major
exemptions for many OTC derivatives – one of the most important of which is foreign
exchange swaps[15]. Of?cial support for banks subsidiaries in a crisis has been made
more dif?cult under the Volcker rule to reduce moral hazard, although this may be
overridden by Congress in a crisis. Origination of new structured products for sale to
clients is certainly permissible under the Volcker rule, despite the complexity and
warehousing required, and the encouragement they give to leverage and tax and
regulatory arbitrage activities. While full separation of proprietary trading as de?ned
is more radical than some of the other proposals, which allow subsidiarisation, it is a
relatively small part of the banking business model. It will not make a suf?cient
difference to the risks in the ?nancial system.
5.B. Vickers
Vickers ring fences the retail bank, and the separated securities entities can be banks
too, setting up as subsidiaries around the world. If a global subsidiary fails, the losses
can be passed up to the parent, equity will be hit, and the creditors of the group (other
than the retail bank) can be bailed in as required. The aim is to ring fence the domestic
retail business from international ?nance and to limit taxpayer costs for losses given
default. It does not reduce risks related to interconnectedness discussed earlier, and the
creditors of one group may essentially pursue those of another.
Bank business
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5.C. Liikanen
Like the OECD, the Liikanen group focuses on removing interconnectedness incentives
while allowing all subsidiaries to remain in a holding company structure. If a bank has
above 15-25 per cent trading securities (trading book plus available for sale securities),
it should be considered for separation. The aim is to limit the TBTF implicit
guarantees, enhance resolvability, and strengthen governance. More capital is needed
for the trading function, but this works via strengthening the Basel risk weighting
approach. Market making should be in the trading entity (unlike Volcker), but
underwriting could stay with the deposit institution. Bail in bonds for the trading
group would require pre-noti?ed bail in bonds. There are two fundamental problems
with this. First, Liikanen has chosen exactly the wrong variable as a threshold for
separation. The above panel regression results show that the trading book plus
available for sale securities are strongly positively related to the DTD – they make a
bank safer not weaker. Derivatives should be the threshold variable. Second, the Basel
risk weighting approach is not correlated with the DTD – a simple leverage ratio
should be preferred.
Other countries such as France and Germany are currently proposing variants of
Liikanen, but with their own “national champion” bank objectives in mind. For
example, the French wish to diverge from Liikanen by allowing market making in the
universal bank. The error in the Liikanen report allows a bank like Deutsche Bank not
to be separated, even though its derivatives are over 40 per cent of their balance sheet,
while trading assets are just under the limit. Puzzlingly, a bank such as Wells Fargo
would (if it were a European bank) be considered for separation, even though only
7 per cent of its portfolio is in GMV (IFRS concept) of derivatives, while having
21 per cent in liquid trading securities – puzzling to say the least.
5.D. Switzerland
Switzerland makes a distinction between separation and separability. Clear
separability will provide incentives to avoid excess leverage and risk. They want
legal separability, combined with stronger capital and liquidity rules that are based on
Basel RWA – and in this sense they sit right within the consensus approach criticised
earlier. Switzerland also provides incentives to resolvability by giving capital
requirement rebates for strong ex ante separability.
6. Conclusion: the OECD proposal for evidence-based separation
The OECD was the ?rst to propose separation as necessary for the future stability of
the ?nancial system (OECD, 2009; Blundell-Wignall et al., 2009). It proposes
a non-operating holding company structure for banks that require separation.
A threshold or benchmark for banks based on the above research is proposed, and once
a bank breaks that threshold the offending securities businesses will be separated from
the traditional bank and ring-fenced from it. The aim of separation is to ensure that the
creditors of one subsidiary cannot pursue those of another, so that the risks undertaken
in all individual subsidiaries would be correctly priced. This means that subsidiaries
cannot trade off the reputation and credit rating of the parent, and this legislation
should be written in a way that cannot be over-ridden by policy makers. The OECD
believes that a bank should be considered for separation if its GMV of derivatives rises
above the 10-15 per cent range, and/or its wholesale funding rises above 30-40 per cent.
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The separated banks would be subject to a simple leverage ratio rule of at least
5 per cent for equity for total (un-weighted assets). The OECD recommendations are
fully consistent with empirical ?ndings on what factors are important in driving banks
to the default point. This distinguishes it from the other approaches. If legislation
cannot be written without regulatory overrides being possible, then full separation of
the entities should apply.
Notes
1. This sample includes the largest publicly traded commercial banks in the USA and in
Europe with total assets that exceed $50bn. The GSIFI banks comprise 21 of the GSIFI
banks in the USA and Europe, as of?cially de?ned by the FSB in November 2011. Banks are
left out where the data did not extend back to 1997.
2. These return ?gures are based on bank reported income and capital, and are notoriously
unreliable due to: income smoothing techniques; discretion in provisioning rules; the
valuation of illiquid assets with the banks’ own models; corporate moral hazard and
regulatory forbearance.
3. A standard deviation of 2 implies a 5 per cent chance of default, which is too high for the
global ?nancial system.
4. See Section 619 of Dodd-Frank (2010).
5. See Duf?e (2012) for the former and GGoodhart (2013) for the latter.
6. Their average total assets and total market capitalisation from 2004 to 2012 are higher than
these of the smaller GSIFI banks as de?ned by the FSB (i.e. Nordea Bank).
7. This set of results adds a further year to this reported in Blundell-Wignall and Roulet (2012).
8. Basel II permitted sophisticated banks to model the riskiness of their own portfolios to
calculate RWA to which the capital rules were applied – an approach that continues under
Basel III. By reducing the ratio of RWA to total assets banks are able to minimise the capital
required to conduct their activities and hence to expand leverage. The change in SEC rules in
2004 allowed investment banks to be supervised on a consolidated entities basis, in place of
the strict SEC limitations on leverage. This was equivalent to the regulatory minimum that
US banks would need to operate in Europe. The huge problems with the move to Basel II
were at the heart of the problem (Blundell-Wignall and Atkinson, 2008, 2010, 2011, 2012;
Blundell-Wignall et al., 2012; Blundell-Wignall and Roulet, 2012).
9. Though not referencing the prior OECD work and commentary on this very issue in
numerous publications since 2008, the BIS has started to look at risk-weight manipulation
via modeling and to take it more seriously (BCBS, 2013).
10. A search of BIS and FSB web sites to 2012 could not ?nd a single paper on business models,
compared to hundreds of papers on capital rule reforms.
11. The idea is to see what ex ante amount of extra capital would be needed, without taking
into account any subsequent impact on s and V that an actual injection of K
*
2 K might have
on s, etc.
12. It is surprising how many economists, bankers and ?nancial analysts point out that these
clearing banks got through the crisis without failing, as though this suggested that the
structures were safe. These views make no allowance for the massive support and bailouts that
banks received from governments (particularly the USA). Allowing AIG to fail for
example could have collapsed the entire edi?ce. This is not the structure that is desirable for
the future.
Bank business
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13. In other words, the delta and gamma of a long-dated interest rate hedge may end up residing
in different silos.
14. When an agent buys a derivative, another agent has to sell a derivative, normally requiring
an opposite market view to the buyer, and/or a very different business objective.
15. Because they are settled without the usual netting.
References
BCBS (2013), Regulatory Consistency Assessment Program (RCAP), BCBS, Basel.
Black, F. and Scholes, M. (1973), “The pricing of options and corporate liabilities”, Journal of
Political Economy, Vol. 81 No. 3.
Blundell-Wignall, A. and Atkinson, P.E. (2008), “The subprime crisis: causal distortions and
regulatory reform”, in Kent, C. and Bloxham, P. (Eds), Lessons from the Financial Turmoil
of 2007 and 2008, Reserve Bank of Australia, Sydney.
Blundell-Wignall, A. and Atkinson, P.E. (2010), “Thinking beyond Basel III: necessary
solutions for capital and liquidity”, OECD Journal: Financial Market Trends, Vol. 2010
No. 1.
Blundell-Wignall, A. and Atkinson, P.E. (2011), “Global SIFI’s, derivatives and ?nancial
stability”, OECD Journal: Financial Market Trends, Vol. 2011 No. 1.
Blundell-Wignall, A. and Atkinson, P.E. (2012), “Deleveraging, traditional versus capital markets
banking and the urgent need to separate GSIFI banks”, OECD Journal: Financial Market
Trends, Vol. 2012 No. 1.
Blundell-Wignall, A. and Roulet, C. (2012), “Business models of banks, leverage and the distance
to default”, OECD Journal: Financial Market Trends, Vol. 2012 No. 2.
Blundell-Wignall, A., Atkinson, P.E. and Roulet, C. (2012), “The business models of large
interconnected banks and the lessons of the ?nancial crisis”, National Institute Economic
Review No. 221.
Blundell-Wignall, A., Wehinger, G. and Slovik, P. (2009), “The elephant in the room: the need to
focus on what banks do”, OECD Journal: Financial Market Trends, No. 2.
Dodd-Frank (2010), Wall Street Reform and Consumer Protection Act.
Duf?e, D. (2012), “Market making under the proposed Volcker rule”, working paper,
Stanford University Graduate School of Business, available at: www.darrellduf?e.com/
uploads/policy/Duf?eVolckerRule.pdf
Goodhart, C.A.E. (2013), “The optimal ?nancial structure”, LSE Financial Markets Group Paper
Series, Special Paper 220.
Gordy, M.B. (2003), “A risk-factor model foundation for ratings-based bank capital rules”,
Journal of Financial Intermediation, Vol. 12 No. 3.
Independent Commission on Banking (2011), Interim Report: Consultation on Reform Options,
Independent Commission on Banking, London, April.
Liikanen, E. (2012), High-Level Expert Group on Reforming the Structure of the EU Banking
Sector – Final Report, European Commission, Brussels.
Merton, R.C. (1977), “On the pricing of contingent claims and the Modigliani-Miller theorem”,
Journal of Financial Economics, Vol. 5, pp. 241-249.
OECD (2009), The Financial Crisis: Reform and Exit Strategies, OECD, Paris (presented to the
2009 London G20 Summit).
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O
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tker-Robe, I., Narain, A., Ilyina, A. and Surti, J. (2011), “The too-important-to-fail conundrum:
impossible to ignore and dif?cult to resolve”, Staff Discussion Note 11/12, International
Monetary Fund, Washington, DC.
Further reading
Chow, J. and Surti, J. (2011), “Making banks safer: can Volcker and Vickers do it?”, Working
Paper No. 11/236, International Monetary Fund, Washington, DC.
Appendix. Distance-to-default
The distance-to-default indicator DTD
t
is the number of standard deviations away from the default
point. To derive the measure, it is assumed that a bank defaults (or is bankrupt) when the market
value of assets equals (or is lower) than the book value of debt (V
t
¼ D
t
). The formula to calculate
the DTD is derived from the option-pricing model of Black and Scholes (1973) and is as follows:
DTD
t
¼
logðV
t
=D
t
Þ þðr
f
2ðs
2
t
=2ÞÞ · T
s
t
????
T
p
where:
V
t
market value of bank’s asset at time t.
r
f
risk-free interest rate.
D
t
book value of the debt at time t.
s
t
volatility of bank’s asset at time t.
T maturity of the debt.
However, the market value of assets (V
t
) and its volatility (s
t
) have to be estimated.
Equity-holders have the residual claim on a ?rm’s assets and have limited liability. As ?rst
realised by Merton (1977), equity can be modelled as a call option on the underlying assets of the
bank, with a strike price equal to the total book value of the bank’s debt. Thus, option-pricing
theory can be used to derive the market value and volatility of bank’s underlying assets from
equity’s market value (VE) and volatility (s
E
), by solving:
V
t
¼
VE
t
þD
t
e
2r
f
T
Nðd2Þ
Nðd1Þ
s
t
¼
VE
t
V
t
s
E;t
Nðd1Þ
where:
d1 ¼
logðV
t
=D
t
Þ þðr
f
þðs
2
t
=2ÞÞ · T
s
t
????
T
p
d2 ¼ d1 2s
t
????
T
p
VE value of bank’s equity.
N the cumulative normal distribution.
s
E
equity’s volatility.
Abank defaults (or is bankrupt) when DTD
t
equals to 0 (or is negative). All data are extracted from
Bloomberg. The total annual debt liabilities (i.e. the difference of the annual total assets and annual
Bank business
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total equity) is interpolated using a cubic spline to yield daily observations (D
t
). The volatility of
equity (s
E
) is the standard deviation of daily return multiplied by
???????
252
p
(i.e. 252 trading days by
year). The expiry date of the option (T) equals the maturity of the debt. Acommon assumption is to
set it to 1. The risk free interest rate (r
f
) is the 12 months interbank rate.
About the authors
Adrian Blundell-Wignall is the Special Advisor to the OECD Secretary General for Financial
Markets, and the Deputy Director of the Directorate of Financial and Enterprise Affairs.
Caroline Roulet is an OECD Economist and Analyst. Caroline Roulet is the corresponding
author and can be contacted at: [email protected]
JFEP
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This article has been cited by:
1. Norbert Gaillard. 2014. Assessing sovereign risk: the case of rich countries. Journal of Financial Economic
Policy 6:3, 212-225. [Abstract] [Full Text] [PDF]
2. Apanard (Penny) Prabha, Clas Wihlborg. 2014. Implicit guarantees, business models and banks’ risk-
taking through the crisis: Global and European perspectives. Journal of Economics and Business . [CrossRef]
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doc_422761167.pdf
The study examines the roles of capital rules, macro variables and bank business models
in determining the safety of banks as measured by the “distance-to-default” (DTD) with the purpose of
drawing implications for regulation of bank capital and business models
Journal of Financial Economic Policy
Bank business models, capital rules and structural separation policies: An evidence-
based critique of current policy trends
Adrian Blundell-Wignall Caroline Roulet
Article information:
To cite this document:
Adrian Blundell-Wignall Caroline Roulet , (2013),"Bank business models, capital rules and structural
separation policies", J ournal of Financial Economic Policy, Vol. 5 Iss 4 pp. 339 - 360
Permanent link to this document:http://dx.doi.org/10.1108/J FEP-06-2013-0025
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Paul Cavelaars, J oost Passenier, (2012),"Follow the money: What does the literature on banking tell
prudential supervisors about bank business models?", J ournal of Financial Regulation and Compliance,
Vol. 20 Iss 4 pp. 402-416http://dx.doi.org/10.1108/13581981211279354
J acopo Carmassi, Richard J ohn Herring, (2013),"Living wills and cross-border resolution of systemically
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Bank business models,
capital rules and structural
separation policies
An evidence-based critique
of current policy trends
Adrian Blundell-Wignall and Caroline Roulet
OECD, Paris, France
Abstract
Purpose – The study examines the roles of capital rules, macro variables and bank business models
in determining the safety of banks as measured by the “distance-to-default” (DTD) with the purpose of
drawing implications for regulation of bank capital and business models.
Design/methodology/approach – Apanel regressionstudyusingpre- andpost-crisis datafor 108US
and European banks is used to explore the issue empirically. Anewtechnique is also used to back out the
amount of capital banks would have needed during the crisis to keep the “DTD” in the very safe zone.
Findings – The simple leverage ratio has a strong relationship with “DTD”, while the Basel ratio
does not. The most important business model features are derivatives and wholesale funding, which
have a strong negative relationship with “DTD”. Trading and available-for-sale securities have a
positive in?uence. Calculations show that it is not possible for any reasonable capital rule to
compensate for the risks created by business model features encompassing large derivative-based
activities. Bank separation policies are essential.
Originality/value – The micro evidence-based analysis as an approach to bank regulation and
business model requirements stands in contrast to the ad hoc way policy has been constructed before
and after the crisis. The empirical evidence supports separation based on the balance sheet size of
derivatives and a leverage ratio instead of the complex Basel risk-weighted capital approach. The
current approaches to structural separation are criticised constructively, and some evidence-based
suggestions for improving bank business models to reduce systemic risk are made.
Keywords Derivatives, Bankbusiness models, Deleveraging, Distance-to-default, Structural separation,
Banking reform, GSIFI banks
Paper type Research paper
1. Introduction
The reasons given for the global ?nancial crisis include too much deregulation, poor
regulation, and ?nancial innovations that led to new trends in structured products and
securitisations involving derivatives and counterparty risks. Securities businesses
expanded rapidly relative to traditional banking based mainly on deposit taking and
lending. Traditional bank lending was based on private information created by the due
diligence of banks, whereas securities businesses operate through capital markets,
The current issue and full text archive of this journal is available at
www.emeraldinsight.com/1757-6385.htm
JEL classi?cation – G01, G15, G18, G20, G21, G24, G28
The views in this paper are those of the authors and do not necessarily re?ect those of any
member government of the OECD. The authors are grateful to Paul Atkinson for comments on
an earlier draft.
Journal of Financial Economic Policy
Vol. 5 No. 4, 2013
pp. 339-360
qEmerald Group Publishing Limited
1757-6385
DOI 10.1108/JFEP-06-2013-0025
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credit ratings and a labyrinth of complex underlying counterparty relationships. Some
of the innovations, where end-users are concerned, were socially useful, but many
others were related to new possibilities for tax and regulatory arbitrage that took the
size of the banking sector and its share of corporate pro?ts to unprecedented levels.
The combined effect of these measures was to undermine effective capital
requirements and to permit an explosion of leverage and interconnectedness within
the ?nancial system that ultimately collapsed upon itself.
The aftermath has seen the ?nancial crisis cause recession and unemployment on a
scale not seen since the great depression, a ?asco that would have been much worse were
it not for the emergency actions of central banks and some treasury authorities in
massive support policies that have no historical benchmarks with which to compare and
assess their long-run effects. These macro cyclical policies are not suitable for
addressing the structural factors that led to the crisis – they were supposed to be
temporary proceeding hand-in-hand with regulatory reform. Unfortunately, the banks
have been successful in pushing back on the two main directions of that reform process:
the needs to raise capital requirements of banks and to reverse the trend in
interconnectedness via the structural separation of bank business models. The banks
favour the Basel risk-weighting approach, which is ineffective, and ?ght hard to exempt
fromseparation the business activities that matter the most. This debate on the needs for
reform has not been informed by empirical research on capital rules that might work to
constrain leverage. Nor has there been evidence to suggest whether business model risk
can be compensated for by capital rules. If some business model features have a large
and independent in?uence on default risk, such that practical capital rules to offset them
are not feasible, then structural separation policies are unavoidable. If so, it is important
to know which business model features are most critical and which are not. The reform
process so far has focused on reforming Basel II into Basel III, and the attempts at
structural separation have taken very different paths (none of which are based on hard
empirical evidence) in the various jurisdictions. The latter include the Dodd-Frank
Volcker rule for the USA, the Vickers review for the UK and the Liikanen group report
for Europe. Switzerland has already adopted a different approach to all of these, and
within Europe countries are already diverging from what Liikanen proposed.
This paper follows up an earlier study by the OECD which was the ?rst to provide
hard empirical evidence on the above issues concerning capital rules and the structural
business model features that drive the default path (Blundell-Wignall and Roulet, 2012).
Section 2 introduces the distance-to-default (DTD) measure, which is the key analytical
tool used to analyse the largest banks in the USA and Europe. The asset-weighted time
series for the DTD is shown, as is the position of US versus European banks in the most
recent year 2012. The empirical evidence presented in Section 3 con?rms the results from
the earlier study. These show that the simple leverage ratio has a strong relationship
with the DTD, while the Basel ratio does not. The main business model features that
matter are derivatives and wholesale funding, which have a strong negative relationship
with the DTD. Trading and available for sale securities on the other hand, because they
enhance liquidity in the face of margin and collateral calls, has a positive relationship
with the DTD. This ?nding is particularly problematic for the recommendations of the
Liikanen group. Anewempirical ?nding is presented in Section 3, which shows that it is
simply not possible for a rational capital rule to compensate for the risks created by
business model features. Section 4 explains how complexity and interdependence
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operates in banks that combine securities businesses (particularly derivatives) with
more traditional banking – it provides examples that illustrate just why the hard
empirical evidence points to derivatives and wholesale funding as the main problem
areas in modern banking. In Section 5, current approaches to structural separation are
criticised constructively. Finally, evidence-based suggestions for separation with the
objective of improving bank business models and, thereby, to reduce systemic risk, are
made in the concluding Section 6.
2. Solvency: the DTD
The DTD is a measure that uses a combination of bank reported data, and market
information to calculate the number of standard deviations a bank is from the default
point, where the market values of assets equals the book value of debt. The formula to
calculate the DTD is derived from the option-pricing model of Black and Scholes (1973)
and is set out as follows:
DTD
t
¼
logðV
t
=D
t
Þ þðr
f
2ðs
2
t
=2ÞÞ · T
s
t
????
T
p ð1Þ
where:
V
t
market value of bank’s asset at time t.
r
f
risk-free interest rate.
D
t
book value of the debt at time t.
s
t
volatility of bank’s asset at time t.
T maturity of the debt.
The calculation is set out in more detail in the Appendix.
Figure 1 shows a time series of the asset-weighted daily DTD calculations of
69 banks, including GSIFI banks, alongside the average quarterly ROE’s, for those in
Europe, the UK and the USA[1].
From 1997 to 2004 the DTD typically averaged three standard deviations. For the
large GSIFI banks, innovations through capital markets securitisation of loans and the
huge demand for structured products to arbitrage the tax system made possible large
hitherto unexploited pro?t opportunities – ROE’s rose sharply from 2002 to 2007[2],
as did the DTD. The main policymaker thinking at this time favoured deregulation for
better ef?ciency and growth, while banks took advantage of this to minimise capital
costs and raise their ROE’s. The DTD, being based on market data gives a more
reliable picture of the likely solvency and liquidity problems of a bank than do ROE’s.
The weighted average DTD fell to 0 in the UK and the USA, implying systemic
insolvency, with many individual banks below the zero point. The DTD fell to below
1 in Europe, with many banks below the solvency point. The USA has recovered more
quickly in 2011-2012, while many European banks are still not at a safe point.
The DTD for individual banks for the most recent year 2012 is shown in Figure 2 for
the same 69 largest US and European banks (the UK and Switzerland are shown with
Europe). It is very clear that the US response to the crisis, with forced capital injections
Bank business
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Figure 1.
Average DTD and
bank ROE’s
–10
–5
0
5
10
15
20
25
0
1
2
3
4
5
6
7
8
9 %
Std Dev.
USA
Weighted DTD ( LHS) Weighted ROE
–15
–10
–5
0
5
10
15
20
0
1
2
3
4
5
6
7
% Std Dev.
Europe
Weighted DTD (LHS) Weighted ROE
–25
–20
–15
–10
–5
0
5
10
15
20
25
0
1
2
3
4
5
6
7
8
D
e
c
-
9
7
A
u
g
-
9
8
A
p
r
-
9
9
D
e
c
-
9
9
A
u
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-
0
0
A
p
r
-
0
1
D
e
c
-
0
1
A
u
g
-
0
2
A
p
r
-
0
3
D
e
c
-
0
3
A
u
g
-
0
4
A
p
r
-
0
5
D
e
c
-
0
5
A
u
g
-
0
6
A
p
r
-
0
7
D
e
c
-
0
7
A
u
g
-
0
8
A
p
r
-
0
9
D
e
c
-
0
9
A
u
g
-
1
0
A
p
r
-
1
1
D
e
c
-
1
1
A
u
g
-
1
2
A
p
r
-
1
3
D
e
c
-
1
3
%
Std Dev.
United Kingdom
Weighted DTD (LHS) Weighted ROE
Source: OECD, Bloomberg
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following proper stress tests on bank assets has led to US banks moving back above
the safe zone of three standard deviations[3].
3. Capital rules versus bank separation
Many European banks and a few US banks need more capital and/or structural
reforms to promote a safer banking system. But the issue that continues to perplex
policy making concerns the right balance between capital rules and business model
reform – where the latter includes the Vickers recommendations
(Blundell-Wignall et al., 2009; Independent Commission on Banking, 2011); the
Dodd-Frank Act Volcker rule[4]; and the Liikanen proposal that is in?uencing
decisions in a number of European countries including France and Germany (Liikanen,
2012). What capital rule works best? Are capital rules enough? And if separation is
important, what is the best way to implement it?
Most international organisations other than the OECD tend to favour improving the
existing system of bank regulation and capital rules, while adding the desire for
“credible” bank resolution regimes to address the too-big-too-fail (TBTF) problem of
the cross-subsidisation of risk. The BCBS and the FSB have focused on replacing Basel
II with Basel III and improved cross-border cooperation. This approach is supported by
IMF studies that argue that the best approach to improve bank safety is:
[. . .] (i) more stringent capital (and possibly liquidity) requirements to limit contribution to
systemic risk; (ii) intensive supervision consistent with the complexity and riskiness of SIFIs;
(iii) enhanced transparency and disclosure requirements to capture emerging risks in the
broader ?nancial system; and (iv) effective resolution regimes at the national and global level
to make orderly resolution a credible option, with resolution plans and tools that lead
creditors to share any losses (O
¨
tker-Robe, 2011, p. 2).
Academics have stressed the dif?culties of interpreting rules based on separation
proposals, and some have been strongly against it[5]. Much of this discussion is based
on literature that predates the crisis, casual empiricism and theoretical argumentation.
But so far the various proposals have not been informed by and based on empirical
Figure 2.
DTD in 2012: the USA
versus Europe
7
6
Std Dev.
US banks European banks
Source: OECD, Bloomberg
5
4
3
2
1
0
1 3 5 7 9 11 13 15 17 19 21 2 4 6 8 10 12 14 16 18 20 22 24 26 28 30 32 34 36 38 40 42 44 46
–1
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research as to what determines sudden moves towards the default point. Nor has there
been any convincing evidence on the type of capital rule that would be enough to make
banks safe.
3.A. Simple capital rules help but independent business-model effects are too powerful
A panel regression approach is used to explain the differences in DTD’s across banks
over the period 2004-2012. The sample consists of the top 100 US and EUinternationally
active commercial banks andbroker-dealers byequitymarket capitalisation. Inaddition,
six banks that failed in the crisis, but which can be considered as GSIFI’s, HBOS,
Merrill Lynch, Lehman Brothers, Washington Mutual, Wachovia and Bear Stearns are
included. There are a total of 108 banks in the sample, consisting of 21 FSB GSIFI banks
(excluding Asian and non-listed banks), six failed former GSIFI banks, two banks with a
system-wide importance in their related countries (i.e., Intesa San Paolo and Banco
Bilbao Vizcaya Argentaria)[6] and 79 other large banks. Only publicly traded banks are
included, because market data are required for the model. The data includes all of the
banks that carry out the counterparty activities in derivatives and other securities that
are a key focus of this study.
The empirical model takes account of the TBTF incentive for excessive risk taking,
macro-prudential in?uences, leverage, and business model aspects. The equation is
estimated with two alternatives for leverage: the leverage ratio and the regulatory
capital approach of the Basel Tier 1 ratio. The empirical model is speci?ed in
equation (1); where the subscripts i and t denote the bank and the period, respectively:
DTD
i;t
¼ /
i;t
þb
1
TA
i;t
þb
2
K
i;t
þb
3
TD
i;t
þb
4
WFD
i;t
þb
5
GMV
i;t
þb
7
BETA
i;t
þb
8
%HPI
i;t
ð2Þ
TA is size variable relating to the TBTF issue, equal to the total assets of the bank as a
share of total assets in the national banking system. It is expected to be inversely related
to the DTD. K corresponds to the simple rule leverage ratio (LEV), which is expected to
have a negative sign, or to the Basel Tier 1 ratio (T1), which is expected to have a positive
sign. The equation is estimated twice, once with LEV, excluding the Basel capital
concept, and once with T1, excluding the simple leverage ratio. TD is the sum of the
trading book and available-for-sale securities, and is expected to have a positive sign.
The reason for this is that liquidity drives the banks’ path to default in practice, when
margin and collateral calls cannot be delivered. Liquid assets can be sold or used as
collateral. WFD refers to wholesale funding as a share of total liabilities and is expected
to have a negative sign – higher wholesale funding typically at a shorter duration is less
stable than deposits for funding longer term assets. GMV refers to the gross market
value of derivatives as a share of the banks’ total assets – appropriately converting all
USbanks to the IFRSconcept for consistency. GMVis expectedto have a negative sign –
this is the quintessential interconnectedness variable where volatility drives rapid
changes in margin requirements. BETA is a macro control variable, de?ned as the
covariance of the ?rm’s stock price with the national stock market, using daily data to
calculate annual observations, divided by the variance of the national stock index.
It is expected to have a negative sign, on the grounds that the ?rm is more connected to
the national macro and asset price cycle. Finally, %HPI refers to the annual percentage
change in the national house price index, and is expected to have a positive sign on
the grounds that rising prices improve a borrower’s equity in the home and vice versa.
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The two equations for the LEVand T1 alternatives are estimated for all banks, the GSIFI
banks and the other large banks in the sample, using ordinary least squares (OLS). After
testing for cross-section versus time-?xed versus random effects, and for the
heteroskedasticity of error, cross-section and time-?xed effects are introduced into the
regression. The regression results are shown in Table I[7].
The simple leverage ratio argument is well determined at the 1 per cent level, for all
banks, the GSIFI banks and the other large bank panels, but the Basel Tier 1 ratio
appears to ?nd no support as a determinant of the DTD in any model. Focusing on the
?rst (LEV) equation the macro control variables in house prices and the market beta are
correctly signed and signi?cant at the 1 per cent level, across all models. With respect to
in?uences on risk taking, the results show that the size of a bank in its own market
(TBTF) is signi?cant at the 1 per cent level for all banks and in the other large
bank samples, but not for the small sample of GSIFI banks only. The reason for this
appears to be that all GSIFI banks are large, and there is less size diversity compared
All banks G-SIFIs banks Other large banks
Constant, a 9.17
* * *
8.26
* * *
11.66
* * *
11.46
* * *
8.52
* * *
7.46
* * *
(18.21) (13.12) (9.02) (8.62) (16.19) (10.48)
TA: bank TA/ntl.
bank assets
23.30
* * *
23.88
* * *
21.70 22.36 26.70
* * *
26.63
* * *
(22.62) (22.74) (21.08) (21.30) (22.92) (22.54)
LEV: TA/bank
equity
20.04
* * *
– 20.03
* * *
– 20.06
* * *
–
(22.97) (22.51) (22.81)
T1: Basel Tier 1
ratio
– 21.31 – 1.24 – 1.57
(0.57) (0.24) (1.14)
TD: trading book
plus available for
sale securities/TA
2.36
* *
1.94
*
3.94
* *
3.73
* *
1.15 0.52
(2.27) (1.79) (2.04) (1.96) (0.97) (0.37)
WFD: wholesale
funding/total
liabilities
22.43
* * *
21.39
* *
26.08
* * *
25.49
* * *
21.70 20.72
(22.78) (21.69) (23.75) (23.29) (21.54) (20.57)
GMV: GMV of
derivatives/TA
25.22
* * *
28.22
* * *
26.16
* * *
28.47
* * *
21.67 25.33
(23.99) (25.73) (23.72) (24.61) (20.67) (21.59)
BETA: CoVar bank
stock ret. with ntl.
mkt ret./var. mkt
22.36
* * *
22.73
* * *
22.80
* * *
23.54
* * *
22.16
* * *
22.05
* * *
(212.26) (212.48) (210.51) (211.49) (29.21) (28.73)
%HPI: House Price
Index ann. %
change
13.18
* * *
16.81
* * *
14.30
* * *
16.58
* * *
13.37
* * *
13.91
* * *
(11.50) (16.12) (8.13) (8.90) (8.96) (10.20)
R
2
0.74 0.72 0.79 0.77 0.72 0.72
Fisher statistic 16.75 14.98 20.30 17.78 14.27 14.15
p-value F 0.00 0.00 0.00 0.00 0.00 0.00
Total observations 728 690 223 205 505 485
Notes: Statistical signi?cant at:
*
10,
* *
5 and
* * *
1 per cent levels; this table shows the results of
estimating multi-variate regressions for an unbalanced panel of 108 US and European internationally
active commercial banks and broker dealers with equity market capitalization in excess of $5bn over
the period 2004-2012; cross-section and time ?xed effects are used in the regressions as is the White
diagonal covariance method
Source: OECD
Table I.
Determinants of bank
DTD: multi-variate
panel results
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to the larger samples. In terms or arguments relating to the business model, the GMV of
derivatives and wholesale funding have the expected negative signs and are signi?cant
at the 1 per cent level for the full sample and for the GSIFI group, but not for the other
large banks (which have only a small derivatives component in their portfolios). Trading
assets have the expected positive signs that ?nd support at the 5 per cent level for the full
sample and the GSIFI banks, but not in a sample that excludes the GSIFI’s.
The evidence suggests that a simple leverage ratio strongly outperforms the complex
risk-weighting approach of the Basel Tier 1 ratio. With regard to business model factors,
the evidence suggests that derivatives and wholesale funding are powerful in?uences on
the DTD which are quite independent of the leverage ratio. These factors appear to be
related mainly to the activities of the GSIFI banks in the sample. These risks can
be ameliorated by the holding of liquid trading securities, which provide liquidity in the
face of margin and collateral calls. However, wrong-way risk in a bout of volatility can
lead to increased margin calls and falling collateral values, in which case the ability to
borrow to fund the gap in the wholesale market is even more critical.
3.B. Explaining why the simple leverage ratio works and why the Basel ratio does not
The Basel Tier 1 ratio applies to risk-weighted assets (RWA), and banks use RWA as a
management tool toreduce the cost of equity, i.e. theyoperate toreduce the ratioof RWAto
TA, enabling leverage to rise even as regulators try to ensure banks have stronger capital
buffers. Under the Basel system total RWA are de?ned (for an 8 per cent Tier 1 ratio) as:
RWA ¼ 12:5 ðOR þMRÞ þ
X
n
i¼1
ðw
i
ÞA
i
ð3Þ
where OR is operational risk, MR is market risk, both of which are grossed up by 12.5 for
8 per cent equivalence, w is an asset risk weight, and A is an asset. This Basel II
representation has been re?ned and added to in Basel III reforms: to raise the quality of
capital; to add buffers for large banks and to add charges for counterparty credit risk (CCR).
By2018banks wouldbe expectedtohave 4.5per cent of RWAas core Tier 1 (close to equity),
and additional equity buffer of 2.5 per cent, adding to 7 per cent (for core Tier 1 plus buffer).
The Tier 1 ratio is set at a 6 per cent minimum. But these reforms do not address
the fundamental criticisms levelled by the OECD on frequent occasions since 2008
(Gordy, 2003):
.
The framework is mathematically based on a single global risk factor for all
banks regardless of their situation – it ignores idiosyncratic risk.
.
The portfolio invariance principle, that risk attributes of any asset are speci?c to
the asset and hence the additivity principle can apply – and hence there is no
Tier 1 penalisation of the concentration of assets.
.
It continues to allow banks to use their own models to estimate VaR’s, their risk
weights and illiquid asset prices (mark to model).
.
Banks can continue to shift the ownership of assets and transform the measured
riskiness of assets via derivatives and SPV’s in the shadow banking system.
.
It does not and cannot deal (see below) with counterparty risk and derivatives.
The Basel rules also permitted banks to use broad concepts of capital to satisfy the
numerator of the Tier 1 ratio (including subordinated debt, hybrids, etc.), instead of
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(costly) pure equity, with each jurisdiction allowing different rules. The announcement of
Basel II in July 2004 (to have been implemented by 2008), and the SEC’s removal of
leverage controls on investment banks, actually encouraged the rapid growth in leverage
and the pro?tability of banks[8]. Figure 3 shows the asset-weighted ratio RWA to total
assets (TA) for 27 GSIFI banks (i.e. 21 GSIFI banks de?ned by the FSB and six former
GSIFI banks that failed in the crisis referred to earlier), and 564 non-GSIFI banks. The use
of models and hedging to lower the ratio of RWA/TA is systematic – banks risk-weight
optimise to minimise the cost of capital and to improve returns for shareholders[9].
Many policy makers at international organisations appear to believe that business
model reform is unnecessary, and that ?nancial stability can be handled by reform of
the capital rules combined with credible resolution mechanisms to deal with TBTF[10].
The problems with derivatives and repos that lead to margin collateral calls cannot be
handled by the Basel III reforms aimed at establishing more capital for banks and the
credit valuation adjustment (CVA) charge to deal with counterparty risk – the
amounts involved are just too large.
In Section 2 it was noted that a DTD minimum of three standard deviations, often
achieved in the late 1990s and early 2000s, is a reasonably safe level where there is only
a very small chance of default. What capital levels would have been enough to
guarantee this level of safety during the crisis period and more recently? To explore
this idea, the DTD model of equation (1) is ?rst solved – see the Appendix. DTD is then
set to 3.0 and (for a maturity of T ¼ 1) target bank capital K
*
is calculated by solving
for the V/D ratio that satis?es that condition for any bank below the critical 3.0
standard deviation threshold:
3:0:s
t
2 r
f
2
s
2
t
2
¼ log
V
t
D
t
¼ /
t
ð4Þ
Given that D ¼ TA 2 K, where TA is total assets, it is then possible to calculate K
*
holding s and V at their original solved values, given the historical observations of
TA:
Figure 3.
RWA to total assets:
GSIFI banks versus
non-GSIFI banks
R
2
= 84%
R
2
= 96%
25
30
35
40
45
50
55
60
65
70
75
2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012
%
G-SIFIs
Non G-SIFIs
Note: Business model risk factors for GSIFI banks cannot be dealt with by
capital rules
Source: OECD, Bloomberg
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The gap K
*
2 K is then computed is computed for each bank and summed over the
system[11]. This gap is calculated for 21 of the GSIFI banks in the USA and in Europe
(de?ned by the FSB, excluding Asian and non-listed banks) and for 48 other large
banks. It is also calculated for the USA, Europe and the UK data separately.
The results for all banks, the GSIFI banks and for the non-GSIFI banks are shown in
Figure 4. From 2002 to 2007 K
*
2 K is not material for most banks, underlining the
point that banks do not need capital, until they need it in a tail event. In 2008, an
additional $2.2tn was needed to keep all bank DTD levels at least at 3.0 standard
deviations, of which $1.6tn was required by the GSIFI banks and $600bn was required
by the other banks. In 2009, $4.5tn more capital was required, of which $3.6 was due to
the GSIFI banks. These amounts then fell away in 2010, and rose again to $600bn in
2011 ($450bn for GSIFI’s). Table II shows some of these amounts in ?gures and
provides a country breakdown. While the US capital needs were greater in 2008 and
2009 ($1.5tn and $2.5tn), Europe and the UK together were only a little less than these
amounts. In recent years the picture has changed substantially with the USA much
farther ahead in the capital raising and asset write-off process.
It is clear from this analysis that in a tail event GSIFI banks are very different to
other large banks. The DTD can rise sharply as margin and collateral calls rise with
volatility. In the worst two years of the crisis The GSIFI banks needed an average of
$2.1tn pa additional capital in 2008 and 2009 according to the DTD analysis. Figure 5
shows the actual changes in collateral demanded in those years for derivative
positions, according to ISDA. From December 2007 to December 2008, the estimated
collateral demanded rose from $2.1tn to $4tn, net rise in collateral demanded was
$1.8tn, and collateral demanded remained at $3.2tn in 2009. These numbers are
illustrative of the actual pressures that the banking system had to bear in the crisis
years relating to derivative margin calls related to trading and the structured product
businesses of mainly GSIFI banks. These were not the only pressures, as non-GSIFI
Figure 4.
The capital needs of banks
through the crisis period
0
500
1,000
1,500
2,000
2,500
3,000
3,500
4,000
4,500
5,000
1997 1998 1999 2000
Source: OECD, Bloomberg
2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012
$
U
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All G-SIFIs Non G-SIFIs
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banks were also drawn into the securitisation and fee-for-sale business model, and the
large numbers seem broadly consistent with the ex ante measures calculated with
the DTD model. This analysis suggests that in a crisis there is no capital rule that will
be feasible before the event – these sums would have meant a capital rule that might
have tripled the capital held by banks prior to the crisis. For many individual GSIFI
banks tripling the capital would not have been suf?cient.
4. The interconnectedness problems with GSIFI banks
GSIFI banks do engage in consumer or retail banking, based on amortised cost
accounting, but their pro?t involvement in investment banking generally, and prime
broking, derivatives and structured product origination, market making and
underwriting, which are based on fair value through or loss (mark-to-market)
accounting, are complex and highly interconnected with other ?nancial institutions. All
of these activities involve inventories of products that are marked to market. In normal
$ billion
2007 2008 2009 2010 2011 2012
Type of bank
Global 13.7 2,225 4,560 363 616 314
G-SIFIs 7.2 1,624 3,611 250 449 203
Non G-SIFIs 6.5 602 949 113 166 111
Domicile of banks
USA 4.9 1,285 2,473 32 176 17
UK 3.2 252 1,075 79 80 53
Europe 5.6 689 1,013 252 359 245
Source: OECD, Bloomberg
Table II.
The capital needs of
banks and regional
breakdown
Figure 5.
The gross credit exposure
(GMV-netting) of
derivatives and collateral
0
1,000
Source: BIS, ISDA, OECD
2,000
3,000
4,000
5,000
6,000
M
a
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Collateral
Gross Credit Exposure
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times risk management tools including netting of exposures, ?nancing through
tri-partite repos, and derivatives hedging work well and do not require much capital and
certainly not any of?cial support. Ina crisis, however, losses fromown activities, failures
of counterparties and the drying-up of liquidity can bring about insolvency that
reverberates through the ?nancial system.
Figure 6 shows some standard functions of such GSIFI banks. This simpli?ed
partial picture of just some of the securities market banking and ?nancing illustrates
just a few of the many issues that arise with counterparty risk.
The top section of Figure 6 shows a typical tri-partite repo transaction. A money
market fund (MMF) in the USA is essentially providing ?nance to a broker dealer in (say)
Europe (an af?liate of a universal bank). This ?nancing tool is interconnected with the
cash needs for the multiple activities of the broker dealer.
A failure of the broker dealer would put the clearing bank at risk with ?ow on effects to
other broker dealers ownedbybanks. These two clearingbanks like central clearingparties
for derivatives (discussedbelow) centralise riskandconnect multiple institutions. Typically
there is not a problem until there is a ?nancial event, in which case liquidity can suddenly
dryup[12]. The MMF(sayfromthe USA) maywithdrawfunds due to excessive exposure to
European banks when liquidity and solvency concerns arise. Concerns about losses in the
MMF could lead to a run on those funds, causing short-term funding to be withdrawn.
In a crisis situation pressure on the lender-of-last resort (LOLR) mechanism to ?ll
the liquidity gap becomes enormous. Injections of capital for the clearer and or the
investment banks in the repo market could be essential in extreme tail events, such as
occurred in 2009.
Figure 6.
Counterparty and
interconnectedness risk
Source: OECD, tri-partite repos
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4.A. Counterparty risk with OTC derivatives
In the middle section of Figure 6, the broker dealer (B-D) is engaging in derivative
transactions with two counterparties hedging its exposure. The overall system is
exposed to the tune of 270. Ignoring the case of the central clearing parties (CCP’s) for
the moment, consider the following examples:
.
There are no defaults, but the B-Dis down a net 20. The crucial point is that this net
20 margin has to be funded, for example, via a short-term repo loan. But in a crisis
situation, this might interact withthe problemof liquidity fromthe normal sources
drying up. The broker dealer cannot meet the margin call, and its parent (without a
?rewall) might try to support it, thereby contaminating other af?liates in the bank
or an insurance company dealing with banks. As AIG, Dexia and others found out,
this contamination can overwhelm the holding company in a crisis. There may be
no reasonable capital rule that could save the institution in a tail risk event.
.
One of the non-bank counterparties wants to unwind the trade during a risk
event (rather than post more collateral) and reset the contract at a higher safer
spread, losing some of its collateral in the process. But in the middle of a crisis
this may prove to be prohibitively expensive, and it may in fact be impossible to
enter a more attractive trade. It may fail, leaving the bank exposed and having to
fund a negative position;, e.g. the 100 owed to the ?rst counterparty.
4.B. Central clearing parties (CCP’s)
The middle of Figure 6 shows the alternative arrangement, provided the derivatives are
standardised, of clearing via a CCP. The regulatory authorities have put a lot of faith inthe
idea that clearing will solve many of the problems that arose in the crisis. Clearing
certainly makes for greater transparency, which is a good thing because it would work to
undermine excessive spreads in the OTC market by improving the scope for price
competition. But CCP’s do not somehow “destroy” risk. Like the clearing banks in a repo
transaction, the CCP needs capital, must model risk and set appropriate margins
commensurate with that risk. In the above trade, at the point in time shown, the net
exposure is 20 for the system, as opposed to gross exposures of 270. But the ability of the
CCP to guarantee the trades depends on its capital which should be suf?cient for all risk
scenarios. It is most important to understand that netting does not in any way mitigate
market risk. A bout of unexpected market volatility may turn the net 20 into something
much larger in a short space of time. The failure of a counterparty would be even more
problematic.
Much the same as a clearing bank in the tri-partite repo market, the CCP will require
sound risk management, and collateralisation via margin calls will need to be appropriate.
Clearing facilitates trading but the market risk remains. The under-pricing of that risk
and TBTF may be signi?cantly worse with a CCP. The CCP becomes a vital node,
interconnecting multiple players in the ?nancial system. The failure of such a node would
lead to multiple contamination effects compared to bilateral trading. In other words, the
problem of TBTF would likely be increased rather than reduced. The central bank and
the taxpayer could not allowthe CCP to fail. It is dif?cult to see howthis feature would not
lead to exactly the same under-pricing of risk that played such a large part in the crisis.
Indeed, competition between CCP’s can only really take the form of reducing collateral
requirements to make the cost of trading cheaper for counterparties, but the clear outcome
will be under-collateralisation and increased risk.
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Furthermore, there is the problem of what can and cannot be cleared. OTC interest
rate derivatives at over $500tn are a huge part of the derivatives market, and more than
half of the $246tn of interest rate swaps are cleared. These typically were not a source
of problem during the crisis. However, derivatives that cannot be cleared were in
the forefront of problems, and the non-cleared derivatives market includes most of
these:
.
Very long–term interest rate swaps (e.g. 15-19 years) sought after by pension
and insurance companies for liability management. A part of this market is
non-standard and cannot be cleared.
.
Single name credit default swaps (CDS), which were so prominent in the
AIG crisis, currently around $30tn. The CDS has the potential for extreme
collateral call shifts when the probability of the default of the reference entity
increases and if default actually occurs, the liability moves to the maximum.
.
Swaptions – options on interest rate swaps (the rights to swap ?xed and
variable interest rates). This is a large market of over $30tn, and is crucial in
managing long-term interest rate risk across many industries. For example, if
rates were thought to rise in the longer run, then a ?rm would have the option
(not obligation) by exercising a swaption to pay ?xed and receive the rising
?oating rate interest payments. These can be up to 30 years maturity and are
highly illiquid. They cannot be eligible for clearing. It was the inability to
manage the risks in this illiquid complex product that caused large losses
for Morgan-Stanley in its joint venture (MUFG) in Japan with Mitsubishi
securities.
.
Some parts of the forward rate agreement market for currencies cannot be
cleared – typically the longer the horizon the more illiquid the market.
.
Parts of the overnight index swap market cannot be cleared. The ?oating rate leg
is based on the reference rate of Fed funds or Libor, and it allows very short-term
borrowers to manage interest rate risk inherent in sudden changes in cost of
funding and income received on longer-term assets.
.
Many OTC commodity, energy and equity derivatives cannot be cleared.
Consider the following example. If a user takes a position in volatility with a swaption,
the trader will typically hedge the market risk in the position with an interest rate
option notional amount equal to some percentage of the swaption (the maturity and
coupon of the swap would mirror those of the swap on which the swaption is based).
But if the swap in mandated to be cleared with the CCP and the swaption is executed
bilaterally, there is no bene?t in clearing the swap from a risk point of view.
The greater complexity may raise risk and will certainly increase collateral costs
compared to keeping the swap and the swaption together bilaterally[13].
In short, there is some risk that clearing will apply to the derivatives which are
plain vanilla, and where risk is small to start with. Mandating CCP’s for low-risk
derivatives will improve transparency but also create a new the TBTF institution;
cause tensions between cleared and non-cleared derivatives to rise; and clearing will
not apply to the illiquid derivatives most likely to be the source of problems in a future
crisis.
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4.C. Supervisory and audit ability in the face of complexity
Finally, the bottom panel of Figure 6 shows an example related to alleged events in a
large GSIFI bank in recent years. The bank sold CDS protection to another
?nancial institution. The bank then hedged itself by buying a super senior tranche:
whereby an asset-backed commercial paper (ABCP) conduit posted collateral with the
bank in the form of a pool of reference assets, and the bank paid it a spread –
essentially the bank bought a put to hedge its CDS position. If the reference
pool of assets falls in value the ABCP conduit owes the bank money and tops up its
margin.
The alleged problem was one of complexity and the inability of the supervisor to
monitor what happened. The bank, before the tail event, did not really buy a put, but
instead bought a put spread with the idea of reducing the cost of protection. The losses
on the worst case scenario envisaged by the bank were, say, 15 per cent of the reference
pool. In such a case the bank could greatly reduce its cost of protection by basing the
premiums to be paid on the case of losses of up to the 15 per cent only. In the crisis,
however, a tail risk event emerged and the losses were much greater than the 15 per cent.
If true, the bank would not be covered, and by IFRS accounting rules the bank would
have to mark the losses to market. Instead, the bank may have accounted the position
based on a put and not the put spread, expecting the reference pool would recover in
value. The question is, can the supervisor and auditor, in practice, monitor at this level of
detail – look at all individual trade tickets and enforce the accounting rules.
Alternatively, there is the risk of regulatory forbearance: the regulator is informed but
works with the bank to avoid disruptive disclosures. Two scenarios are then possible:
(1) the asset pool recovers and whistle blower revelations fall on the deaf ears of the
involved authority; or
(2) the asset pool does not recover, and the bank risks major losses and possible
failure if it cannot fund the net position.
4.D. In summary: macro cyclical tools cannot solve structural issues
In all of these cases complexity and interdependence are the problem during a risk tail
event. There are so many players, and the pressure may come from any part of the
market and affect all the other parts. Liquidity can freeze up from a number of different
pressures and take down the ?nancial system in the absence of emergency policies.
Any of the counterparties may fail for a variety of reasons, or be unable to perform
their functions, resulting in margin calls not being funded. TBTF problems remain and
new one may be created with CCP’s. Forms of fraud and/or regulatory forbearance may
be present. Runs on deposits in MMF’s may be the driving point. Since the business
models of banks have not been fundamentally altered, the main lifting to deal with the
crisis has been cyclical liquidity policies. This in turn can lead to a new set of problems
by rekindling asset prices and leverage in securities markets, setting up for new
versions of the crisis later on. In short, the fundamental structural problem of business
model reform has not been dealt with. During the crisis, the contamination effect to
traditional banking functions of deposit taking and lending to consumers and small
and medium-sized businesses has been a prime causal factor in the recession and the
record unemployment in many jurisdictions.
Addressing the problems of ?awed bank business models and losses with cyclical
tools such as low interest rates, compressing the term premium, and emergency
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lending certainly helps banks but does not deal with the structural issues. If persisted
with for a long period, such policies will shift the bubble around to new sectors, such as
higher yielding corporate debt and to re?ate bank securities and structured products
back towards pre-crisis levels. If the response to the crisis is mainly cyclical and the
banks remain too large, too complex and too interconnected to fail, then risk will
continue to be under-priced, and little real reform will have been achieved. Figure 3
shows the asset-weighted balance sheets of banks in the USA, Europe and the UK.
5. The need for structural separation and current proposals
Banks argued successfully for the repeal of US separation policies that limited their
international business models. Just when European universal banks might have
bene?tted from the separation of traditional and investment banking, the regulatory
and business model trends were in exactly the opposite direction. The main drivers of
bank lobbying in this regard were the pro?tability of leverage, high OTC derivative
spreads, and the business model need to have suf?cient diversity of market views and
scale amongst derivative counterparties[14]. The above analysis shows that business
models have evolved to such a complex and interconnected state that there is no
reasonable capital rule that can be in place in normal times to protect the ?nancial
system in the event of major defaults and related bouts of market volatility.
The amounts of capital required to keep the DTD above three in a crisis are simply too
large. The panel regression results also showed that the DTD is sensitive only to the
simple leverage ratio and not the Basel ratio, while business model features have
strong independent effects on the DTD.
The Basel reforms for counterparty risk may be summarised as follows:
.
A CCR capital buffer based on expected exposures with a stress test of value at
risk in a market event that affects the probability of default of a counterparty –
which has the effect of raising RWA.
.
ACVA, which is an additional up-front charge to cover mark-to-market unexpected
counterparty losses (working through the MR term in the above equation 3). The
CVA is calculated by netting set, and is additive across netting sets.
.
In addition Basel is designed to encourage use of CCP’s and exchange traded
products, where reductions in capital cost can be achieved.
These Basel add-on proposals are subject to all the problems with modelling and moral
hazard noted earlier. But in addition to these, the CVA charge applies at the netting set
level, and is additive across netting sets. Like other aspects of Basel that have led to
problems in the past, the approach does not reward diversi?cation. A large number of
netting pools will give rise to less scope for cross-product netting, and more positive
and negative positions that will add to a positive CVA charge. If larger GSIFI banks
choose to deal more and more with each other, they increase the scope for cross-product
netting and reduce the CVA charge. Hence, the Basel rule encourages more
concentration in derivatives – it increases the TBTF problem in derivatives rather
than reducing it. Furthermore, netting is best suited to settlement process concepts –
netting provides no protection for market risk. Basing capital rules on netting pools –
encouraged by banks – is not in the interests of the future stability of the ?nancial
system. These rules will certainly not cause suf?cient capital to be held to compensate
for the absence of structural separation. As noted before, the panel regression results
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suggest that simple capital rules help, but they cannot compensate for the large impact
on the DTD of business model features. This brings the discussion back to the
necessity of structural separation and where the lines for separation should be drawn.
Indeed, the bank regulators paradox is that large complex and interconnected banks
need very little capital in the good times, but they can never have enough in an
extreme crisis. Separation is required to deal with this problem. The point of separation
is to avoid the cross-subsidisation from implicitly insured TBTF banks to securities
af?liates (of meaningful size) that engage in risking the banks own capital and liquidity
status in counterparty transactions with other institutions. These activities involve
derivatives and related products that require ready access to repo and other short-term
funding to meet margin and collateral calls which, in a crisis, may not be forthcoming for
all institutions; and hence the path to default (without of?cial support) can be
particularly rapid and spread between ?rms. Having such risk activities occur between
ring-fenced af?liates or separate ?rms that are not implicitly insured will be much less
serious, as market discipline will then ensure the correct pricing of risk through
appropriate segregations and margin requirement procedures. Supply and demand for
the activity will be commensurate with its underlying riskiness when the ability to
resolve the (smaller and separate) ?rm is credible in the eyes of all participants.
5.A. Volcker
The Volcker rule is complex and asks for rules to be written that depend on the intent
of a trader: servicing a client for a fee without speculating on short-term price
movements against which there is a blanket ban. Banks successfully argued that the
Volcker rule should continue to allow underwriting and market making, in spite of a
blanket ban on speculating on short-term price movements with the banks’ own
balance sheet – yet both of these activities involve banks taking inventory of assets,
the extent of which requires them to make a book and hedge speculations on future
price movements of that inventory. The banks have also succeeded in achieving major
exemptions for many OTC derivatives – one of the most important of which is foreign
exchange swaps[15]. Of?cial support for banks subsidiaries in a crisis has been made
more dif?cult under the Volcker rule to reduce moral hazard, although this may be
overridden by Congress in a crisis. Origination of new structured products for sale to
clients is certainly permissible under the Volcker rule, despite the complexity and
warehousing required, and the encouragement they give to leverage and tax and
regulatory arbitrage activities. While full separation of proprietary trading as de?ned
is more radical than some of the other proposals, which allow subsidiarisation, it is a
relatively small part of the banking business model. It will not make a suf?cient
difference to the risks in the ?nancial system.
5.B. Vickers
Vickers ring fences the retail bank, and the separated securities entities can be banks
too, setting up as subsidiaries around the world. If a global subsidiary fails, the losses
can be passed up to the parent, equity will be hit, and the creditors of the group (other
than the retail bank) can be bailed in as required. The aim is to ring fence the domestic
retail business from international ?nance and to limit taxpayer costs for losses given
default. It does not reduce risks related to interconnectedness discussed earlier, and the
creditors of one group may essentially pursue those of another.
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5.C. Liikanen
Like the OECD, the Liikanen group focuses on removing interconnectedness incentives
while allowing all subsidiaries to remain in a holding company structure. If a bank has
above 15-25 per cent trading securities (trading book plus available for sale securities),
it should be considered for separation. The aim is to limit the TBTF implicit
guarantees, enhance resolvability, and strengthen governance. More capital is needed
for the trading function, but this works via strengthening the Basel risk weighting
approach. Market making should be in the trading entity (unlike Volcker), but
underwriting could stay with the deposit institution. Bail in bonds for the trading
group would require pre-noti?ed bail in bonds. There are two fundamental problems
with this. First, Liikanen has chosen exactly the wrong variable as a threshold for
separation. The above panel regression results show that the trading book plus
available for sale securities are strongly positively related to the DTD – they make a
bank safer not weaker. Derivatives should be the threshold variable. Second, the Basel
risk weighting approach is not correlated with the DTD – a simple leverage ratio
should be preferred.
Other countries such as France and Germany are currently proposing variants of
Liikanen, but with their own “national champion” bank objectives in mind. For
example, the French wish to diverge from Liikanen by allowing market making in the
universal bank. The error in the Liikanen report allows a bank like Deutsche Bank not
to be separated, even though its derivatives are over 40 per cent of their balance sheet,
while trading assets are just under the limit. Puzzlingly, a bank such as Wells Fargo
would (if it were a European bank) be considered for separation, even though only
7 per cent of its portfolio is in GMV (IFRS concept) of derivatives, while having
21 per cent in liquid trading securities – puzzling to say the least.
5.D. Switzerland
Switzerland makes a distinction between separation and separability. Clear
separability will provide incentives to avoid excess leverage and risk. They want
legal separability, combined with stronger capital and liquidity rules that are based on
Basel RWA – and in this sense they sit right within the consensus approach criticised
earlier. Switzerland also provides incentives to resolvability by giving capital
requirement rebates for strong ex ante separability.
6. Conclusion: the OECD proposal for evidence-based separation
The OECD was the ?rst to propose separation as necessary for the future stability of
the ?nancial system (OECD, 2009; Blundell-Wignall et al., 2009). It proposes
a non-operating holding company structure for banks that require separation.
A threshold or benchmark for banks based on the above research is proposed, and once
a bank breaks that threshold the offending securities businesses will be separated from
the traditional bank and ring-fenced from it. The aim of separation is to ensure that the
creditors of one subsidiary cannot pursue those of another, so that the risks undertaken
in all individual subsidiaries would be correctly priced. This means that subsidiaries
cannot trade off the reputation and credit rating of the parent, and this legislation
should be written in a way that cannot be over-ridden by policy makers. The OECD
believes that a bank should be considered for separation if its GMV of derivatives rises
above the 10-15 per cent range, and/or its wholesale funding rises above 30-40 per cent.
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The separated banks would be subject to a simple leverage ratio rule of at least
5 per cent for equity for total (un-weighted assets). The OECD recommendations are
fully consistent with empirical ?ndings on what factors are important in driving banks
to the default point. This distinguishes it from the other approaches. If legislation
cannot be written without regulatory overrides being possible, then full separation of
the entities should apply.
Notes
1. This sample includes the largest publicly traded commercial banks in the USA and in
Europe with total assets that exceed $50bn. The GSIFI banks comprise 21 of the GSIFI
banks in the USA and Europe, as of?cially de?ned by the FSB in November 2011. Banks are
left out where the data did not extend back to 1997.
2. These return ?gures are based on bank reported income and capital, and are notoriously
unreliable due to: income smoothing techniques; discretion in provisioning rules; the
valuation of illiquid assets with the banks’ own models; corporate moral hazard and
regulatory forbearance.
3. A standard deviation of 2 implies a 5 per cent chance of default, which is too high for the
global ?nancial system.
4. See Section 619 of Dodd-Frank (2010).
5. See Duf?e (2012) for the former and GGoodhart (2013) for the latter.
6. Their average total assets and total market capitalisation from 2004 to 2012 are higher than
these of the smaller GSIFI banks as de?ned by the FSB (i.e. Nordea Bank).
7. This set of results adds a further year to this reported in Blundell-Wignall and Roulet (2012).
8. Basel II permitted sophisticated banks to model the riskiness of their own portfolios to
calculate RWA to which the capital rules were applied – an approach that continues under
Basel III. By reducing the ratio of RWA to total assets banks are able to minimise the capital
required to conduct their activities and hence to expand leverage. The change in SEC rules in
2004 allowed investment banks to be supervised on a consolidated entities basis, in place of
the strict SEC limitations on leverage. This was equivalent to the regulatory minimum that
US banks would need to operate in Europe. The huge problems with the move to Basel II
were at the heart of the problem (Blundell-Wignall and Atkinson, 2008, 2010, 2011, 2012;
Blundell-Wignall et al., 2012; Blundell-Wignall and Roulet, 2012).
9. Though not referencing the prior OECD work and commentary on this very issue in
numerous publications since 2008, the BIS has started to look at risk-weight manipulation
via modeling and to take it more seriously (BCBS, 2013).
10. A search of BIS and FSB web sites to 2012 could not ?nd a single paper on business models,
compared to hundreds of papers on capital rule reforms.
11. The idea is to see what ex ante amount of extra capital would be needed, without taking
into account any subsequent impact on s and V that an actual injection of K
*
2 K might have
on s, etc.
12. It is surprising how many economists, bankers and ?nancial analysts point out that these
clearing banks got through the crisis without failing, as though this suggested that the
structures were safe. These views make no allowance for the massive support and bailouts that
banks received from governments (particularly the USA). Allowing AIG to fail for
example could have collapsed the entire edi?ce. This is not the structure that is desirable for
the future.
Bank business
models
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13. In other words, the delta and gamma of a long-dated interest rate hedge may end up residing
in different silos.
14. When an agent buys a derivative, another agent has to sell a derivative, normally requiring
an opposite market view to the buyer, and/or a very different business objective.
15. Because they are settled without the usual netting.
References
BCBS (2013), Regulatory Consistency Assessment Program (RCAP), BCBS, Basel.
Black, F. and Scholes, M. (1973), “The pricing of options and corporate liabilities”, Journal of
Political Economy, Vol. 81 No. 3.
Blundell-Wignall, A. and Atkinson, P.E. (2008), “The subprime crisis: causal distortions and
regulatory reform”, in Kent, C. and Bloxham, P. (Eds), Lessons from the Financial Turmoil
of 2007 and 2008, Reserve Bank of Australia, Sydney.
Blundell-Wignall, A. and Atkinson, P.E. (2010), “Thinking beyond Basel III: necessary
solutions for capital and liquidity”, OECD Journal: Financial Market Trends, Vol. 2010
No. 1.
Blundell-Wignall, A. and Atkinson, P.E. (2011), “Global SIFI’s, derivatives and ?nancial
stability”, OECD Journal: Financial Market Trends, Vol. 2011 No. 1.
Blundell-Wignall, A. and Atkinson, P.E. (2012), “Deleveraging, traditional versus capital markets
banking and the urgent need to separate GSIFI banks”, OECD Journal: Financial Market
Trends, Vol. 2012 No. 1.
Blundell-Wignall, A. and Roulet, C. (2012), “Business models of banks, leverage and the distance
to default”, OECD Journal: Financial Market Trends, Vol. 2012 No. 2.
Blundell-Wignall, A., Atkinson, P.E. and Roulet, C. (2012), “The business models of large
interconnected banks and the lessons of the ?nancial crisis”, National Institute Economic
Review No. 221.
Blundell-Wignall, A., Wehinger, G. and Slovik, P. (2009), “The elephant in the room: the need to
focus on what banks do”, OECD Journal: Financial Market Trends, No. 2.
Dodd-Frank (2010), Wall Street Reform and Consumer Protection Act.
Duf?e, D. (2012), “Market making under the proposed Volcker rule”, working paper,
Stanford University Graduate School of Business, available at: www.darrellduf?e.com/
uploads/policy/Duf?eVolckerRule.pdf
Goodhart, C.A.E. (2013), “The optimal ?nancial structure”, LSE Financial Markets Group Paper
Series, Special Paper 220.
Gordy, M.B. (2003), “A risk-factor model foundation for ratings-based bank capital rules”,
Journal of Financial Intermediation, Vol. 12 No. 3.
Independent Commission on Banking (2011), Interim Report: Consultation on Reform Options,
Independent Commission on Banking, London, April.
Liikanen, E. (2012), High-Level Expert Group on Reforming the Structure of the EU Banking
Sector – Final Report, European Commission, Brussels.
Merton, R.C. (1977), “On the pricing of contingent claims and the Modigliani-Miller theorem”,
Journal of Financial Economics, Vol. 5, pp. 241-249.
OECD (2009), The Financial Crisis: Reform and Exit Strategies, OECD, Paris (presented to the
2009 London G20 Summit).
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O
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tker-Robe, I., Narain, A., Ilyina, A. and Surti, J. (2011), “The too-important-to-fail conundrum:
impossible to ignore and dif?cult to resolve”, Staff Discussion Note 11/12, International
Monetary Fund, Washington, DC.
Further reading
Chow, J. and Surti, J. (2011), “Making banks safer: can Volcker and Vickers do it?”, Working
Paper No. 11/236, International Monetary Fund, Washington, DC.
Appendix. Distance-to-default
The distance-to-default indicator DTD
t
is the number of standard deviations away from the default
point. To derive the measure, it is assumed that a bank defaults (or is bankrupt) when the market
value of assets equals (or is lower) than the book value of debt (V
t
¼ D
t
). The formula to calculate
the DTD is derived from the option-pricing model of Black and Scholes (1973) and is as follows:
DTD
t
¼
logðV
t
=D
t
Þ þðr
f
2ðs
2
t
=2ÞÞ · T
s
t
????
T
p
where:
V
t
market value of bank’s asset at time t.
r
f
risk-free interest rate.
D
t
book value of the debt at time t.
s
t
volatility of bank’s asset at time t.
T maturity of the debt.
However, the market value of assets (V
t
) and its volatility (s
t
) have to be estimated.
Equity-holders have the residual claim on a ?rm’s assets and have limited liability. As ?rst
realised by Merton (1977), equity can be modelled as a call option on the underlying assets of the
bank, with a strike price equal to the total book value of the bank’s debt. Thus, option-pricing
theory can be used to derive the market value and volatility of bank’s underlying assets from
equity’s market value (VE) and volatility (s
E
), by solving:
V
t
¼
VE
t
þD
t
e
2r
f
T
Nðd2Þ
Nðd1Þ
s
t
¼
VE
t
V
t
s
E;t
Nðd1Þ
where:
d1 ¼
logðV
t
=D
t
Þ þðr
f
þðs
2
t
=2ÞÞ · T
s
t
????
T
p
d2 ¼ d1 2s
t
????
T
p
VE value of bank’s equity.
N the cumulative normal distribution.
s
E
equity’s volatility.
Abank defaults (or is bankrupt) when DTD
t
equals to 0 (or is negative). All data are extracted from
Bloomberg. The total annual debt liabilities (i.e. the difference of the annual total assets and annual
Bank business
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total equity) is interpolated using a cubic spline to yield daily observations (D
t
). The volatility of
equity (s
E
) is the standard deviation of daily return multiplied by
???????
252
p
(i.e. 252 trading days by
year). The expiry date of the option (T) equals the maturity of the debt. Acommon assumption is to
set it to 1. The risk free interest rate (r
f
) is the 12 months interbank rate.
About the authors
Adrian Blundell-Wignall is the Special Advisor to the OECD Secretary General for Financial
Markets, and the Deputy Director of the Directorate of Financial and Enterprise Affairs.
Caroline Roulet is an OECD Economist and Analyst. Caroline Roulet is the corresponding
author and can be contacted at: [email protected]
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