Session 1: Bank Risk and Regulatory Implications I Chair: Clas Wihlborg, CBS

1. Session 1: Bank Risk and Regulatory Implications I Chair: Clas Wihlborg, CBS Asia Link Programme Research Conference on “Safety and Efficiency of the Financial System” Manila Aug. 27, 2007

2. The Papers • The Determinants of Domestic and Cross Border Bank Contagion Risk in South East Asia • Carlos Bautista, Philippe Rous, Amine Tarazi • The Effects of NPLs on Bank Lending Behaviour: A Threshhold Model • David Dickinson, Yixin Hon • The Use of Accounting and Stock Market Data to Predict Bank Financial Distress: A Case Study of Asian Banks • Isabelle Distinguin, Jocelyn Trinidad, Amine Tarazi

3. The Theme • The risk of a bank’s failure is particularly serious as a result of potential contagion among banks and repercussions on the real economy. • Paper 1: The potential for contagion within and among S.E. Asian countries’ banking systems • Paper 2: Real sector repercussions of distress (non-performing loans above a threshold level) • Paper 3: Predicting distress in banking (and thereby possibly prevent systemic effects)

4. The Determinants of Domestic and Cross Border Bank Contagion Risk in South East Asia; Comments • 1. Defining and Measuring Systemic Risk and Contagion • 2. The magnitude of correlations; Evidence of (lack of) contagion risk? • 3. The contributions of individual banks to contagion

5. Systemic risk and contagion Events in the financial sector cause substantial real effects contributing to a recession or depression or, if events originating in the real sector are amplified by the financial system, then we have a systemic risk problem. • Causality goes from Fin’l system • Systemic effect requires either extreme concentration in the financial sector or contagion within the financial sector. Q-marks w.r.t. correlations in the paper: 1.Correlation between two banks’ stock returns (adjusted for market) need not be evidence of potential contagion though linkages, but could be caused by similarity of exposures 2. The causes of correlation in normal times need not be the main sources of contagion in a crisis

6. Correlations • DOMC: yearly mean of correlations between weekly “abnormal stock returns” of banks within country (alternatives tested as well, including correlations for large movements) • CBMC: yearly mean for one country’s banks’ correlations with banks in other countries • Sensitivity of country DOMC/CBMC to individual bank’s DOMC(i)/CBMC(i) • >1: “overreaction in terms of contagion” ?? • Explaining sensitivity: Dummy for sensitivity>1 with statistical significance. • LARGE number of accounting and market variables describing bank.

7. Observations on correlations • High/low DOMC countries seem unrelated to crisis or not in 97 • Even high ones for DOMC rather low (.2-.3) in terms of average probability of move in the same direction • Averages for CBMC close to zero • What does high sensitivity for a bank really mean?

8. Correlations and sensitivities • Regressions explain high sensitivities • Why not some selectivity among bank characteristics on theoretical grounds? • Based on sources of interbank-contagion and opaqueness instead of only collinearity • Alternative: Find high correlation banks (pairwise) in order to find characteristics explaining correlations (is the procedure used a substitute for this?--we lack data on pair-wise relations). • Interactive terms: Explain • Interpretations: Stepwise procedure eliminating variables with collinearity is perhaps more appropriate for forecasting than for explaining.

9. The Effects of NPLs on Bank Lending Behaviour: A Threshhold Model • Major concern: Banks with large non-performing loans are unwilling to lend, presumably because they are constrained by capital requirements or inability to obtain funding. Relevance for procyclicality debate. • BUT: Limited liability and (implicit or explicit) deposit insurance provides incentives to “gamble for resurrection”

10. Questions on NPLs • Non-performng loans • Bad data? • To what extent has capital been reduced correspondingly? (provisions) • To what extent are banks required to hold capital against recognized NPLs • The general question is to what extent NPL has an effect on behavior distinct from effect of capital?

11. Specification • Are growth rates defined for each variable or are loans, deposits, capital defined relative to some variable? • Simultaneity? • Interactions in addition to capital ratio dummy? • Threshholdeffect: Interesting but alterntives can be considered: quadratic variable, interactions • Is specification of effective capital ratio also derived from threshold analysis?

12. Results • Surprising differences across countries • I would like to see alternative specifications before I’m convinced

13. The Use of Accounting and Stock Market Data to Predict Bank Financial Distress: A Case Study of Asian Banks • The most “ready to go” of the papers in the session. • General question: How can financial distress be measured? Downgrading? Why not Accounting measures (NPL and the like)? Why not Stock market returns? • One issue is where information about the shape of the bank appears first: What predicts what? • Thus, the issue here is what predicts ratings.

14. Comments • Focus on predictions rather than explanations. One must go to the back to see what variables mean. • However, analysis of size and structure effects has greater economic content. Interesting. • Would it be possible to do out-of sample tests?

15. Does the following make sense? • Accounting and market indicators are good predictors of upgrades but not downgrades for large banks. Market indicators predict downgrades but not upgrades for small banks.