claudio giannotti , university lum casamassima , bari [email protected]

Liquidity risk exposure for specialized and unspecialized real estate banks: evidence from

the Italian market

Claudio Giannotti, University LUM Casamassima, [email protected]

Lucia Gibilaro, University of [email protected]

Gianluca Mattarocci, University of Rome “Tor Vergata” [email protected]

Milano – June 23td-26th , 2010

Introduction

Literature review

Empirical analysis:

Sample

Methodology

Results

Conclusions

Index

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)

N° of banks in the sample respect to the overall Italian banking sector

Total assets managed by banks in the sample respect the overall Italian banking sector

Source: Bank of Italy and ABI banking data processed by the authors

Database: ABI banking dataTime horizon: 2000-2007 Frequency of data: yearly

Mean85%

Mean 92%

Empirical analysis: Sample (2/2)

Number of REBS respect to the overall sample

Number of years in which each bank is classified as REBS

Following Blasko and Sinkey (2006), we identify REBs on the basis of the ratio between real estate loanS and total assets (threshold 40%)

Mean 47%

>= 4 years55%

Empirical analysis: Methodology (1/3)

Matz and Neu, 2007

Duttweiler, 2009

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.

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.

Threshold100%

Threshold100%

Empirical analysis: Methodology (2/3)

Item Implemented proxy Factor appliedStock of high quality liquid assets Cash Cash 100% Qualifying marketable securities from sovereigns, central banks, public sector entities, and multi-lateral development banks

Government Bonds qualified for refinancing operations by the Central Bank

100%

Qualifying central bank receivables Reserves above the minimum requirement by the Central Bank

100%

Domestic sovereign or central bank debt in domestic currency Domestic sovereign or central bank debt in domestic currency

100%

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 AA- No proxy implementation 80% 60% 80% 60% Total value of stock of highly liquid assets Cash Outflows Retail deposits: - stable deposits Deposits minimum 7.5% - less stable retail deposits [additional categories to be determined by jurisdiction]

Deposits minimum 15%

Unsecured wholesale funding: - Stable, small business customers Deposits minimum 7.5% - Less stable, small business customers [additional categories to be determined by jurisdiction]

Deposits minimum 15%

- non-financial corporates, no operational relationship Deposits 75% Secured funding:

Funding from repo of illiquid assetsand securities lending/borrowingtransactions illiquid assets are lent out

No proxy implementation

Amounts receivable from retailcounterparties

Retail overdrafts

Amounts receivable from wholesalecounterparties

Bank overdrafts

LR

Available Stable Funding (Sources)Implemented proxy

Required Stable Funding (Uses)Implemented proxy

ItemFactor applied

ItemFactor 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

100%

• 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

• Cash • Short-term unsecured actively-traded instruments (< 1 yr) • Securities with exactly offsetting reverse repo • Securities with remaining maturity < 1 yr • Non-renewable loans to financials with remaining maturity < 1 yr

0%

CashSecurities hold for trading

• Stable deposits of retail and small business customers (non-maturity or residual maturity < 1yr)

85%

Retail deposits • Debt issued or guaranteed by sovereigns, central banks, BIS, IMF, EC, non-central government, multilateral development banks

5%

Governement securities

• Less stable deposits of retail and small business customers (non-maturity or residual maturity < 1yr)

70%

Retail deposits • Unencumbered non-financial senior unsecured corporate bonds (or covered bonds) rated at least AA, maturity ≥ 1 yr

20%

Proxy not implemented

• Wholesale funding provided by non-financial corporate customers (non-maturity or residual maturity < 1yr)

50%

Wholesale counterparties lines of credit

• Unencumbered listed equity 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

50%

Proxy not implemented

Gold

Overdrafts

• All other liabilities and equity not included above

0% • All other liabilities and equity not included above

• Loans to retail clients having a maturity < 1 yr

85% Overdrafts

• All other assets 100% All other assets

Empirical analysis: Methodology (3/3) NSFR

Empirical analysis: Results (1/3)

Overall Others REBs2000 0.5021852 0.48819 0.7339772001 0.6454966 0.642017 0.5144052002 0.7204958 0.721337 0.3298572003 0.6330587 0.637834 0.5168242004 0.6799326 0.679066 0.683572005 0.360547 0.792391 0.8885162006 0.7816827 0.770818 0.9165892007 0.4262781 0.390197 0.87259

Table 1. The relationship between numerator and the denominator of the LR

Overall Others REBs2000 0.9878589 0.988648 0.878052001 0.8834786 0.881602 0.9006982002 0.9640367 0.973604 0.4105652003 0.9416667 0.953117 0.7635582004 0.8333647 0.81503 0.9816942005 0.7017364 0.94508 0.6570082006 0.9452888 0.946085 0.9381862007 0.8810365 0.881283 0.905621

Table 2. The relationship between numerator and the denominator in the NFSR

Mean correlation

No REBs = 64%REBS = 68%

Mean correlation

No REBs = 92%REBS = 80%


Table 3. LR statistics for REBs and other banks

2007 2006 2005 2004Others REBs Others REBs Others REBs Others REBs

Obs. 480 201 501 173 60 52 274 417

Mean 0.041742 0.949895 -0.050091 -0.029173 -0.07065 -2.528212 -0.274128 -1.055678Dev. St. 4.002711 14.39675 0.423905 0.375364 0.182969 18.11419 28.01242 1.999414Min -28.2635 -0.46581 -1.52095 -0.73525 -1.35221 -130.631 -177.177 -25.2574Max 82.16451 204.0404 7.461202 3.298246 0.152333 1.218638 235.5864 16.10463

Z Prob (Z) Z Prob (Z) Z Prob (Z) Z Prob (Z)WilcoxonH0:

REBs=Others0.337 0.7365 0.439 0.6609 1.202 0.2294 1.656 0.0977


Obs. 295 396 394 327 435 307 406 324

Mean -0.779914 -1.037483 -2.709711 -0.940388 -18.00083 -2.822106 -7.18094 -1.169203Dev. St. 22.52245 -1.578356 18.78792 1.235592 332.4167 32.92222 55.89433 -.657854Min -96.7952 18.6258 -211.225 -6.3373 -6909.37 -577.442 -759.539 -19.5909Max 292.0024 5.325306 109.9227 8.247646 379.5905 4.947193 157.8445 3.772888

Z Prob (Z) Z Prob (Z) Z Prob (Z) Z Prob (Z)WilcoxonH0 :

REBs=Others-1.304 0.1922 -0.462 0.6439 -1.327 0.1845 -2.799 0.0051



Obs. 490 204 513 176 63 59 277 417Mean 0.156246 0.198587 0.026239 0.026075 0.168163 0.243124 4.333631 1.103696Dev. St. 0.154231 0.674863 0.073279 0.074239 0.13683 0.176268 31.12509 0.341244Min -0.01469 0 0 -0.00066 -4.2E-07 0 0 0.058694Max 1.128477 9.558944 0.524784 0.438073 0.493425 0.949356 441.6486 3.083993


REBs=Others-0.667 0.5051 0.135 0.8928 -2.411 0.0159 0.369 0.7121


Obs. 301 396 401 328 445 307 410 324Mean 1.345172 1.57536 2.802334 1.654038 2.04268 1.085733 1.244891 1.158526Dev. St. 21.54399 9.140028 29.12589 10.26566 20.75772 0.316148 3.92765 0.366567Min -283.895 0.046824 -11.8329 0.049221 -60.0217 0.050401 -73.85 0.05041Max 236.989 182.8631 582.6147 186.9272 434.0665 2.024204 15.108 2.542183


REBs=Others1.471 0.1412 -0.055 0.956 -0.537 0.591 1.269 0.2043

Table 4 – NSFR statistics for REBs and other banks

Index

Introduction

Literature review

Empirical analysis:

Sample

Methodology

Results

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.

Conclusions

Claudio GiannottiUniversity of LUM Casamassimae-mail: [email protected]

Lucia GibilaroUniversity of Bergamoe-mail: [email protected]

Gianluca MattarocciUniversity of Rome Tor Vergatae-mail: [email protected]

Contact information

claudio giannotti , university lum casamassima , bari [email protected]

Documents

banks liquidity position

market liquidity risk

funding liquidity risk

liquidity risk exposure

unexpected liquidity

market risk

vulnerability of banks

n of banks