Transcript Economia del Mercato Mobiliare

Liquidity risk exposure for specialized and
unspecialized real estate banks: evidence from
the Italian market
Claudio Giannotti, University LUM Casamassima, Bari
[email protected]
Lucia Gibilaro, University of Bergamo
[email protected]
Gianluca Mattarocci, University of Rome “Tor Vergata”
[email protected]
Milano – June 23td-26th , 2010
Index
 Introduction
 Literature review
 Empirical analysis:
 Sample
 Methodology
 Results
 Conclusions
Introduction
 Liquidity is the ability of a bank to fund increases in
assets and meet obligations as they come due, without
incurring unacceptable losses and the maturity
transformation of short-term deposits into long-term loans
makes banks inherently vulnerable to liquidity risk (Basel
Committee on Banking Supervision, 2008).
 The vulnerability of banks toward liquidity risk is
determined by the funding risk and the market risk (The
Joint Forum, 2006). The funding liquidity risk is caused
either by the maturity mismatch between inflows and
outflows or the sudden and unexpected liquidity needs
due to contingency conditions (Duttweiler, 2009). The
market liquidity risk refers to the inability to sell assets at
or near the fair value (Matz and Neu, 2007).
Introduction
Research question:
- Due to the characteristics of the service offered, is there
any specific feature for the liquidity of the real estate
banks (hereinafter REBs)?
- Regulatory provision considers the specific features of
the REBs in constructing supervisory rules for the
banking system?
Index
 Introduction
 Literature review
 Empirical analysis:
 Sample
 Methodology
 Results
 Conclusions
Literature review (1/2)
The behaviour toward liquidity is affected by firms
characteristics: banks liquidity position is affected by both
the size, the status type and the product type.
The size affects the attitude of the bank toward wholesale
funding, including the access opportunity (Allen et al., 1989)
and the price of the funds obtained (Nyborg et al., 2002).
The product type offered to the counterparties, both on the
assets and liabilities side, are able to affect the liquidity
position: banks that take on demand deposits and offer loan
commitments need to hold higher liquid buffers that can be
mitigated if a non perfect correlation holds (Kashyap et al.,
2002).
Literature review (2/2)
REBs invest in assets that at their origination are illiquid:
even though real estates are liquid in the sense of the
market microstructure theory, they can fail to provide
liquidity when the firm need it (Holmstroem and Tirole, 2000)
and, such illiquidity, is affected by the economic cycle
(Krainer, 1999).
Beyond the illiquidity of the assets at their origination, REBs
show an average maturity of assets that is higher than the
one of liabilities, even though they show better maturity
interest rate gaps than unspecialized banks (Blasko and
Sinkey, 2006).
Index
 Introduction
 Literature review
 Empirical analysis:
 Sample
 Methodology
 Results
 Conclusions
Empirical analysis: Sample (1/2)
Database: ABI banking data
Time horizon: 2000-2007
N° of banks in the sample respect to the
overall Italian banking sector
Frequency of data: yearly
Total assets managed by banks in the sample
respect the overall Italian banking sector
Mean
92%
Mean
85%
Source: Bank of Italy and ABI banking data processed by the authors
Empirical analysis: Sample (2/2)
Following Blasko and Sinkey (2006), we identify REBs on the
basis of the ratio between real estate loanS and total assets
(threshold 40%)
Number of REBS respect to
the overall sample
Number of years in which each bank is
classified as REBS
Mean
47%
>= 4 years
55%
Empirical analysis: Methodology (1/3)
Threshold
100%
Matz and Neu, 2007
The liquidity coverage ratio identifies the amount of unencumbered, high
quality liquid assets an institution holds that can be used to offset the net cash
outflows it would encounter under an acute short-term stress scenario
specified by supervisors.
Threshold
100%
Duttweiler, 2009
The net stable funding ratio measures the amount of longer-term, stable
sources of funding employed by an institution relative to the liquidity profiles of
the assets funded and the potential for contingent calls on funding liquidity
arising from off-balance sheet commitments and obligations.
Empirical analysis: Methodology (2/3)
Item
Stock of high quality liquid assets
Cash
Qualifying marketable securities from sovereigns, central banks, public
sector entities, and multi-lateral development banks
Qualifying central bank receivables
Domestic sovereign or central bank debt in domestic currency
In addition, the Committee will gather data on the following instruments to
analyse the impact of this standard on the financial sector: Qualifying
corporate bonds rated AA or higher Qualifying corporate bonds rated A- to
AA-Qualifying covered bonds rated AA or higher Qualifying covered bonds
rated A- to AATotal value of stock of highly liquid assets
Cash Outflows
Retail deposits:
- stable deposits
- less stable retail deposits [additional categories to be determined by
jurisdiction]
Unsecured wholesale funding:
- Stable, small business customers
- Less stable, small business customers [additional categories to be
determined by jurisdiction]
- non-financial corporates, no operational relationship
Secured funding:
Funding from repo of illiquid assets
and securities lending/borrowing
transactions illiquid assets are lent out
Amounts receivable from retail
counterparties
Amounts receivable from wholesale
counterparties
Implemented proxy
Factor applied
Cash
Government Bonds qualified for
refinancing operations by the Central
Bank
Reserves above the minimum
requirement by the Central Bank
Domestic sovereign or central bank
debt in domestic currency
100%
100%
No proxy implementation
80% 60% 80% 60%
Deposits
Deposits
minimum 7.5%
minimum 15%
Deposits
Deposits
minimum 7.5%
minimum 15%
Deposits
75%
No proxy implementation
Retail overdrafts
Bank overdrafts
100%
100%
LR
Empirical analysis: Methodology (3/3)
Available Stable Funding (Sources)
Factor
Item
applied
• Tier 1 & 2 Capital Instruments
• Other preferred shares and
capital instruments in excess of
Tier 2 allowable amount having
an effective maturity of one
year or greater • Other
liabilities with an effective
maturity of 1 year or greater
• Stable deposits of retail and
small business customers
(non-maturity or residual
maturity < 1yr)
• Less stable deposits of retail
and small business customers
(non-maturity or residual
maturity < 1yr)
• Wholesale funding provided
by non-financial corporate
customers (non-maturity or
residual maturity < 1yr)
• All other liabilities and equity
not included above
100%
Required Stable Funding (Uses)
Factor
Item
applied
• Tier 1 & 2 Capital Instruments • Cash • Short-term unsecured
• Other preferred shares and
actively-traded instruments (< 1 yr) •
capital instruments in excess of Securities with exactly offsetting
Tier 2 allowable amount having reverse repo • Securities with
0%
an effective maturity of one
remaining maturity < 1 yr • Nonyear or greater • Other
renewable loans to financials with
liabilities with an effective
remaining maturity < 1 yr
maturity of 1 year or greater
Implemented proxy
• Debt issued or guaranteed by
sovereigns, central banks, BIS, IMF,
EC, non-central government,
multilateral development banks
Retail deposits
• Unencumbered non-financial senior
unsecured corporate bonds (or
covered bonds) rated at least AA,
maturity ≥ 1 yr
Wholesale counterparties lines • Unencumbered listed equity
of credit
securities or non-financial senior
unsecured corporate bonds (or
covered bonds) rated at least A-,
maturity ≥ 1 yr
• Gold
• Loans to non-financial corporate
clients having a maturity < 1 yr
• All other liabilities and equity • Loans to retail clients having a
not included above
maturity < 1 yr
• All other assets
Retail deposits
85%
70%
50%
0%
NSFR
Implemented proxy
Cash
Securities hold for trading
Governement securities
5%
Proxy not implemented
20%
Proxy not implemented
50%
Gold
Overdrafts
85%
100%
Overdrafts
All other assets
Empirical analysis: Results (1/3)
Table 1. The relationship between numerator and the denominator of the LR
2000
2001
2002
2003
2004
2005
2006
2007
Overall
0.5021852
0.6454966
0.7204958
0.6330587
0.6799326
0.360547
0.7816827
0.4262781
Others
0.48819
0.642017
0.721337
0.637834
0.679066
0.792391
0.770818
0.390197
REBs
0.733977
0.514405
0.329857
0.516824
0.68357
0.888516
0.916589
0.87259
Mean correlation
No REBs = 64%
REBS = 68%
Table 2. The relationship between numerator and the denominator in the NFSR
2000
2001
2002
2003
2004
2005
2006
2007
Overall
0.9878589
0.8834786
0.9640367
0.9416667
0.8333647
0.7017364
0.9452888
0.8810365
Others
0.988648
0.881602
0.973604
0.953117
0.81503
0.94508
0.946085
0.881283
REBs
0.87805
0.900698
0.410565
0.763558
0.981694
0.657008
0.938186
0.905621
Mean correlation
No REBs = 92%
REBS = 80%
Empirical analysis: Results (2/3)
Table 3. LR statistics for REBs and other banks
2007
Obs.
Mean
Dev. St.
Min
Max
Wilcoxon
H0:
REBs=Others
2006
Mean
Dev. St.
Min
Max
Wilcoxon
H0
:
REBs=Others
2004
Others
480
REBs
201
Others
501
REBs
173
Others
60
REBs
52
Others
274
REBs
417
0.041742
4.002711
-28.2635
82.16451
Z
0.949895
14.39675
-0.46581
204.0404
Prob (Z)
-0.050091
0.423905
-1.52095
7.461202
Z
-0.029173
0.375364
-0.73525
3.298246
Prob (Z)
-0.07065
0.182969
-1.35221
0.152333
Z
-2.528212
18.11419
-130.631
1.218638
Prob (Z)
-0.274128
28.01242
-177.177
235.5864
Z
-1.055678
1.999414
-25.2574
16.10463
Prob (Z)
0.337
0.7365
0.439
0.6609
1.202
0.2294
1.656
0.0977
2003
Obs.
2005
2002
2001
2000
Others
295
REBs
396
Others
394
REBs
327
Others
435
REBs
307
Others
406
REBs
324
-0.779914
22.52245
-96.7952
292.0024
-1.037483
-1.578356
18.6258
5.325306
-2.709711
18.78792
-211.225
109.9227
-0.940388
1.235592
-6.3373
8.247646
-18.00083
332.4167
-6909.37
379.5905
-2.822106
32.92222
-577.442
4.947193
-7.18094
55.89433
-759.539
157.8445
-1.169203
-.657854
-19.5909
3.772888
Z
Prob (Z)
Z
Prob (Z)
Z
Prob (Z)
Z
Prob (Z)
-1.304
0.1922
-0.462
0.6439
-1.327
0.1845
-2.799
0.0051
Empirical analysis: Results (3/3)
Table 4 – NSFR statistics for REBs and other banks
2007
Obs.
Mean
Dev. St.
Min
Max
Wilcoxon
H0 :
REBs=Others
2006
Wilcoxon
H0 :
REBs=Others
2004
Others
490
0.156246
0.154231
-0.01469
1.128477
REBs
204
0.198587
0.674863
0
9.558944
Others
513
0.026239
0.073279
0
0.524784
REBs
176
0.026075
0.074239
-0.00066
0.438073
Others
63
0.168163
0.13683
-4.2E-07
0.493425
REBs
59
0.243124
0.176268
0
0.949356
Others
277
4.333631
31.12509
0
441.6486
REBs
417
1.103696
0.341244
0.058694
3.083993
Z
Prob (Z)
Z
Prob (Z)
Z
Prob (Z)
Z
Prob (Z)
-0.667
0.5051
0.135
0.8928
-2.411
0.0159
0.369
0.7121
2003
Obs.
Mean
Dev. St.
Min
Max
2005
2002
2001
2000
Others
301
1.345172
21.54399
-283.895
236.989
REBs
396
1.57536
9.140028
0.046824
182.8631
Others
401
2.802334
29.12589
-11.8329
582.6147
REBs
328
1.654038
10.26566
0.049221
186.9272
Others
445
2.04268
20.75772
-60.0217
434.0665
REBs
307
1.085733
0.316148
0.050401
2.024204
Others
410
1.244891
3.92765
-73.85
15.108
REBs
324
1.158526
0.366567
0.05041
2.542183
Z
Prob (Z)
Z
Prob (Z)
Z
Prob (Z)
Z
Prob (Z)
1.471
0.1412
-0.055
0.956
-0.537
0.591
1.269
0.2043
Index
 Introduction
 Literature review
 Empirical analysis:
 Sample
 Methodology
 Results
 Conclusions
Conclusions
• Even though REBs bank hold illiquid assets and are
featured by an average assets maturity higher than the
average liabilities maturity, they do not show to hold a lower
level of liquidity with respect to other banks
• Especially for REBs that securitize real estate loans,
measure to evaluate the liquidity degree of the bank should
deserve more relevance to the off balance sheet exposures
that are able to drain the liquidity obtained through the sale
of the assets and to re –allocate transferred risks back to the
originator but potentially under different environment
conditions.
Contact information
Claudio Giannotti
University of LUM Casamassima
e-mail: [email protected]
Lucia Gibilaro
University of Bergamo
e-mail: [email protected]
Gianluca Mattarocci
University of Rome Tor Vergata
e-mail: [email protected]