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Is the Comprehensive Assessment really comprehensive?

Is the Comprehensive Assessment really comprehensive?. R. Baviera, Politecnico Milano, Nicola Bruti Liberati QFinLab E. Barucci, Politecnico Milano, Nicola Bruti Liberati QFinLab C. Milani , Centro Europa Ricerche Paris, VIII Financial Risks International Forum, March 30-31, 2015.

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Is the Comprehensive Assessment really comprehensive?

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  1. Is the Comprehensive Assessment really comprehensive? R. Baviera, Politecnico Milano, Nicola Bruti Liberati QFinLab E. Barucci, Politecnico Milano, Nicola Bruti Liberati QFinLab C. Milani, Centro Europa Ricerche Paris, VIII Financial Risks International Forum, March 30-31, 2015

  2. Outline • Comprehensive Assessment • Asset Quality Review (AQR) and Stress Tests (ST); • The role of shortfall. • The analysis • Research questions; • Dataset; • Reference model. • Results • Main results; • Further results; • Is the Comprehensive Assessment really comprehensive?

  3. Premise: CA & Shortfall Comprehensive Assessment AQR ST • AQR and ST exercises have different goals: • AQR aims to define a level playing field in the Euro area as a basis for ECB supervision • ST aims to determine the soundness of banks (evaluate their risks) • We focus on determinants of AQR & ST shortfall (SF) in abs values • (Thresholds: AQR 8%, ST baseline scenario 8%, ST adverse scenario 5.5%) • Tobit regressions

  4. Research Questions (I) • Banking union/new supervisory approach • Is new approach coherent with NCA? • Does ECB apply double standards (core-non core countries, national champions, financial assets-credit activity)? • Does the ECB trust IRB models? • Bank capital • Are risk weighted capital ratios informative of bank’s risk (leverage vs CET ratio)? • Large variation in RWAs not driven by banks’ business models and risk profiles • (e.g. EBA (2013), Le Leslé & Avramova (2012), Haldane (2011), Acharya et al. (2014)) • Are IRB models used to manipulate RWA? (e.g. Mariathasan & Merrouche (2014)) • Is the CA really comprehensive? • Acharya et al. (2014) on EBA 2011 ST, Acharya & Steffen (2014) on 2014 CA • adopting the SRISK measure (market based): • the adjustment should be much higher than the one computed by the CA • SF computed w.r.t. a RWA capital ratio is negatively related to SRISK

  5. Research Questions (II) Acharya & Steffen (2014)

  6. Dataset • dataset at bank level from ECB, w.r.t. AQR and ST shortfalls: 129 banks in euro area • dataset from EBA w.r.t. credit risk & market risk information:103 banks • country specific macroeconomic variables: • Indexes of bank regulatory framework in the different European countries (see Barth, Caprio and Levine (2001) for more details) from World Bank database • Government support to European financial institutions after 2007 crisis: at bank level (Mediobanca, 2014) & at country level (Eurostat) • stock prices & market capitalizations for listed banks (Thomson Reuters)

  7. Reference model • We focus on AQR SF & adverse scenario ST SF considering a set of exogenous variables: • cet: common equity Tier 1 ratio • npe: non-performing credit exposure over total exposure (performing & non-performing) • cr (quality indicator of balance sheet): cover ratio for npe • sys (national champion ): ratio of bank’s assets over country GDP • mktCap: stock exchange capitalization over GDP (country index) • Dirb: dummy, 1 if more than 50% or RWA computed with an internal model • rwa (risk density): RWA over Total Assets • lr (leverage ratio): equity over total asssets

  8. Main results: Shortfall in AQR (table 4)

  9. Main results: Shortfall in ST (table 5)

  10. Main results: AQR Relevant • leverage is an important indicator, high SF for hi-leveraged banks (coherent with B3) • most significant SF for medium size banks (confirmed in ST) • systemic role of a bank is associated with a smaller SF (confirmed in ST) • a well developed financial market negatively affects AQR SF • SF inflated by the ratio of npe. • Phenomenon balanced by a high coverage ratio which negatively affects SFs Not-Relevant • rwa (risk density) only marginally statistically significant with a positive coefficient • level 3

  11. Main results: ST ST regressions confirm main results provided by AQR with two main differences: • While it is confirmed that a high leverage ratio is negatively related to the shortfall, cet1 ratio no more a significant variable. • While it is confirmed that a high npe is positively related to the shortfall, • coverage ratio no more statistically significant.

  12. Main results: role of IRB models • Banks with a high risk density relying on IRB are more less exposed to AQR SF. • An IRB with a high risk density is considered reliable in AQR. • Banks with a small risk density relying on IRB are more exposed to ST SF. • Some evidence of manipulation by banks with a low capital level in ST. Derivative of SF w.r.t. DIRB AQR ST

  13. Further results: Home bias • AQR SF is positively & significantly affected by the concentration of the banking activity in the country where the bank is incorporated. Effect mostly concentrated on large banks: for both credit exposure & government bonds (notice that the latter were not part of the review). • Curiously enough, ST SF not affected by the non diversification of the banking activity.

  14. Further results: Home bias on SF in the AQR (table 10)

  15. Further results: Core vs non core countries • The dummy DCORE for banks incorporated in the countries: • Austria, Belgium, Germany, Finland, France, Luxembourg, Netherland. • DCORE is significant in AQR but not in ST: • AQR SFs are higher in case of a non core country. • ST adverse scenario didn’t penalize non core countries. • This interpretation is confirmed by the interactions between • 1-DCORE, DCORE and CET1, LR, NPE, CR, SYS • The coefficients of the interaction with CET1 and LR negative and stat. significant • Higher npe or cr in core countries are associated to a small SF, the opposite non core

  16. Further results: Core vs non core countries AQR (table 12)

  17. Further results: Core vs non core countries ST adverse (table 13)

  18. Is the CA really comprehensive? CA weaknesses on the market side • Inadequate information set • Valuation of Level 3 assets • Off balance sheet items • Methodology • PD & LGD impacts only on CVA

  19. Is the CA really comprehensive? Level 3 assets Assets (blns) Impact (blns) 0.2 1.4 Negligible! The valuation revision seems inadequate for assets that • present scanty liquidity • involve complex features • For Derivatives' set the impact is €0.2 bln (60% for Banque populaire Caisse d’Epargne)

  20. Is the CA really comprehensive? Off balance sheet items A bank in the sample TACRR: 1440 blns TA incl. Off bal.sheet Total Assets: 1580 blns Regulatory arbitrage Off balance sheet: 200 blns …AQR credit provisions amounted to €0.2 bln The interpretation of the regulation does not appear adequate to enhance transparency.

  21. Is the CA really comprehensive? Methodology Probabilities of Default (PD) & Loss Given Default (LGD) • 27% Increase in CVA The supervisor considered inadequate PD & LGD PD & LGD also the main ingredients in IRB models: however no adj. of RWA weights in AQR …a further evidence of RWA manipulation

  22. Does the CA capture bank risk? We consider for the 41 listed banks in EBA sample • the historical volatility Jan-Oct 2014 (as market risk measure) • the capital deficit that emerges from CA as a percentage of CET1 (2013) • We find a positive relation of vol vs capital deficit, in contrast with Acharya and Steffen (2014) • Some market risk is caught by CA, although evaluated on a risk weights-based threshold

  23. Conclusions • Banking union/new supervisory approach • CA concentrated on the traditional credit activity rather than on banks’ fin. assets • IRB: Evidence of manipulation of RWA for less capitalized banks • Double standards in AQR (not in ST): core-non core, credit-finance, home bias • Defence of national champions in the AQR • Bank capital • Risk adjusted bank capital: not so useful to capture risk. Leverage is superior. • Post CA or post capital issuances leverage captures risk, CET ratio doesn’t • Is the CA really comprehensive? • No role played by banks’ fin. assets • Level 3 assets and off balance sheet items ignored • It is considered inadequate PD & LGD in CVA but no evaluation of impact on IRB • CA captures some risk: capital shortfall is related to market volatility

  24. Bibliography sketch [1] V. Acharya, R. Engle & M. Richardson (2014) Testing macroprudential stress tests: the risk of regulatory risk weights, Journal of Monetary Economics, 65: 36-53 [2] V. Acharya & S. Steffen (2014) Benchmarking the European Central Bank’s asset quality review and stress test: a tale of two leverage ratios, VOX, November 2014 [3] E. Barucci, R. Baviera & C. Milani (2014) Is the Comprehensive Assessment Really Comprehensive?, Available at ssrn.com/abstract=2541043 [4] J.R. Barth, G. Caprio & R. Levine (2001) The regulation and supervision of banks around the world - a new database, World Bank Policy Research Working Paper 2588. [5] F. Cannata, S. Casellina & G. Guidi (2012) Inside the labyrinth of Basel risk weighted assets: how not to get lost, Bank of Italy, occasional paper nr. 132 [6] European Banking Authority (2013) Interim results update of the EBA review of the consistency of risk weighted assets, available on http://goo.gl/IeNuwX [7] A. Haldane (2011) Capital discipline, Bank of England, mimeo [8] V. Le Leslé & S. Avramova (2012) Revisiting risk-weighted assets, IMF working paper, 12/90 [9] M. Mariathasan & O. Merrouche (2014) The manipulation of Basel risk-weights, Journal of Financial Intermediation, 23: 300-321

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