Claudio Giannotti , University LUM Casamassima , Bari giannotti@lum.it

1. Liquidity risk exposure for specialized and unspecialized real estate banks: evidence from the Italian market Claudio Giannotti, University LUM Casamassima, Bari giannotti@lum.it Lucia Gibilaro, University of Bergamo lucia.gibilaro@unibg.it Gianluca Mattarocci, University of Rome “Tor Vergata” gianluca.mattarocci@uniroma2.it Milano – June 23td-26th , 2010

2. Index • Introduction • Literature review • Empirical analysis: • Sample • Methodology • Results • Conclusions

3. 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).

4. 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?

5. Index • Introduction • Literature review • Empirical analysis: • Sample • Methodology • Results • Conclusions

6. 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).

7. 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).

8. Index • Introduction • Literature review • Empirical analysis: • Sample • Methodology • Results • Conclusions

9. Empirical analysis: Sample (1/2) Database: ABI banking data Time horizon: 2000-2007 Frequency of data: yearly Mean 92% Mean 85% Source: Bank of Italy and ABI banking data processed by the authors

10. 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%) Mean 47% >= 4 years 55%

11. 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.

12. LR Empirical analysis: Methodology (2/3)

13. NSFR Empirical analysis: Methodology (3/3)

14. Empirical analysis: Results (1/3) Table 1. The relationship between numerator and the denominator of the LR Meancorrelation No REBs = 64% REBS = 68% Table 2. The relationship between numerator and the denominator in the NFSR Meancorrelation No REBs = 92% REBS = 80%

15. Empirical analysis: Results (2/3) Table 3. LR statistics for REBs and other banks

16. Empirical analysis: Results (3/3) Table 4 – NSFR statistics for REBs and other banks

17. Index • Introduction • Literature review • Empirical analysis: • Sample • Methodology • Results • Conclusions

18. 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.

19. Contact information Claudio Giannotti University of LUM Casamassima e-mail: giannotti@lum.it Lucia Gibilaro University of Bergamo e-mail: lucia.gibilaro@unibg.it Gianluca Mattarocci University of Rome Tor Vergata e-mail: gianluca.mattarocci@uniroma2.it