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Comparison of Bank Credit Ratings Assigned by Rating Agencies. Alexander Karminsky Vladimir Sosyurko Alexander Vasilyuk National Research University “ Higher School of Economics” Moscow , Russia. EBES 2011 CONFERENCE - ISTANBUL June, 1-3. Agenda.
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Comparison of Bank Credit Ratings Assigned by Rating Agencies Alexander Karminsky Vladimir Sosyurko Alexander Vasilyuk National Research University “Higher School of Economics” Moscow, Russia EBES 2011 CONFERENCE - ISTANBUL June, 1-3
Agenda • Problem of credit rating comparison • Rating agencies in Russia • Multiple mapping of rating scales. Concept & Development • Data gathering & Results • Conclusion Karminsky, Sosyurko, Vasilyuk - Comparison of Bank Credit Ratings Assigned by Rating Agencies EBES 2011 CONFERENCE - ISTANBUL
Purpose and constraints of credit ratings • Ratings are the independent estimates of: • financial performance of companies, banks or financial instruments • issuer’s creditworthiness (credit risk) • admission to various market products or activity • Ratings are the interest for business entities and market participants, as far as for the authorities and regulating organizations (Central Banks, Ministries of Finance, Deposit Insurance Agencies, etc.) • Limitations and constraints for ratings: • Low number of current relevant ratings • Problem of rating comparison for different rating agencies • Absence of multiplicative effect from presence of competitor’s rating estimations • Requirement for expanded use of independent rating estimations Karminsky, Sosyurko, Vasilyuk - Comparison of Bank Credit Ratings Assigned by Rating Agencies EBES 2011 CONFERENCE - ISTANBUL
Problem of rating comparison • Most relevant: • Possibility of comparison of various agency ratings • Diversified estimations with use of rating modeling • Lacks: • Only pair comparisons are used, scales’ correspondences are incompatible, displays are linear and use of econometric potential is limited • No settled approaches to rating scales comparison • Conclusion: required considering all restrictions on arrangement, data accessibility, etc. Karminsky, Sosyurko, Vasilyuk - Comparison of Bank Credit Ratings Assigned by Rating Agencies EBES 2011 CONFERENCE - ISTANBUL
Rating agencies in Russia 7 agencies = 3 international & 4 national 596 ratings at the end of 2010 Number of bank ratings 259 358 454 604 596 2006 2007 2008 2009 2010 Karminsky, Sosyurko, Vasilyuk - Comparison of Bank Credit Ratings Assigned by Rating Agencies EBES 2011 CONFERENCE - ISTANBUL
Concept of multiple mapping • Increase of comparison reliability of scales mapping by using all available statistical information (in time, on agencies, scales and structures) • Development of the database that includes ratings, financial and macro-indicators • Econometric exposure of the most significant publicly accessible explanatory variables that have an influence on ratings • Creation of a base scale for mapping transformation of all compared agency-ratings • Building up a criteria of scales correspondence, considering the peculiarities of explained component • Determination of mapping parameters using the optimization procedures. Carrying out the comparison of rating scales • Verification of criteria and estimation of parameters for scales conformity. Analysis of time dynamics and trends • Forming the methodical and practical basis for regular monitoring, modeling and verification of rating models Karminsky, Sosyurko, Vasilyuk - Comparison of Bank Credit Ratings Assigned by Rating Agencies EBES 2011 CONFERENCE - ISTANBUL
NS1 RS1 F1(α1) RatingScales NumericScales Fi(αi) BS RSi NSi Base Scale RSN FN(αN) NSN Comparison methods and base scale • Comparison methods for rating scales include: • Methodology and principles of mapping of rating scales • Criteria for comparison of rating scales (Mathematics) • Econometric models for scales’ comparison • Audit of the “conformity table” and the coordination of its structure • Comparison methods are concluded to have: • Choice of a base rating scale • Mapping system for displaying external and internal ratings into a base scale • Application to each class of rating entities (banks, companies, etc.) • Allowing simultaneous use of all independent rating estimations Karminsky, Sosyurko, Vasilyuk - Comparison of Bank Credit Ratings Assigned by Rating Agencies EBES 2011 CONFERENCE - ISTANBUL
Rating modeling (Ordered probit models) where xi– is a set of independent variables • Rating is a depended variable y • Less values of y are connected with higher agency-ratings • Ratings are represented as a numeric scale: 12+ grades Karminsky, Sosyurko, Vasilyuk - Comparison of Bank Credit Ratings Assigned by Rating Agencies EBES 2011 CONFERENCE - ISTANBUL
Research data • 10 rating scales: • 4 national rating agencies • 3 international agencies (3+3) • Time period: 1q2006 – 4q2010 (20 quarters) • 370 Russian bankswith at least 1 rating during this period • Total 7400 observations of banks Karminsky, Sosyurko, Vasilyuk - Comparison of Bank Credit Ratings Assigned by Rating Agencies EBES 2011 CONFERENCE - ISTANBUL
Numerical scales Karminsky, Sosyurko, Vasilyuk - Comparison of Bank Credit Ratings Assigned by Rating Agencies EBES 2011 CONFERENCE - ISTANBUL
Criteria for choosing the mapping function Q– set of allobservations {t – period of time, j – bank, Ri1jt– Moody’s rating (base scale), Ri2jt– rating of another agency } t = 1, … , T j = 1, …., K Fi1 : Ri → Rbase Fi = αi1 ∙ fi (Ri) + αi2 fi – linear, polynomial, logarithmic function that transforms rating into a base scale Karminsky, Sosyurko, Vasilyuk - Comparison of Bank Credit Ratings Assigned by Rating Agencies EBES 2011 CONFERENCE - ISTANBUL
Mapping function Multiple mapping into the base scale: • linear • logarithmic • polynomial (up to 5th power) Moody’s – S&P Moody’s – Moody’s (rus) Karminsky, Sosyurko, Vasilyuk - Comparison of Bank Credit Ratings Assigned by Rating Agencies EBES 2011 CONFERENCE - ISTANBUL
Logarithmic model of multiple mapping Logarithmic model for2006-2010 years: Moody’s credit ratings (R) and default probabilities (PD) of banks are approximatedby a logarithmic dependence during the years 1980-2008 M = const∙Ra↔ Ln(M) = a∙Ln(R)+b PD = 0,000218×R3,8 PD(%) R Karminsky, Sosyurko, Vasilyuk - Comparison of Bank Credit Ratings Assigned by Rating Agencies EBES 2011 CONFERENCE - ISTANBUL
Rating comparison (logarithmic scales) NRA Rus-Rating Expert RA AK&M Fitch (rus) Fitch S&P (rus) S&P Moody’s (rus) Moody’s Karminsky, Sosyurko, Vasilyuk - Comparison of Bank Credit Ratings Assigned by Rating Agencies EBES 2011 CONFERENCE - ISTANBUL
Comparison of international banks • 3639 pairs(Moody’s – another agency) • Bank data 1995 – 2010 • 290 different banks Fitch S&P Moody’s Credit rating’ comparison for scales of international agencies(logarithmic model) Karminsky, Sosyurko, Vasilyuk - Comparison of Bank Credit Ratings Assigned by Rating Agencies EBES 2011 CONFERENCE - ISTANBUL
Conclusion • Econometric models for ratings play significant role due to IRB Approach and other Basel II recommendations and should be developed • Scientific and practical basis of using econometric rating models for bank risk management is discussed • Comparison method of ratings of different agencies lies in the basis of Unified Rating Space modeling system • Scales Mapping Concept and methods are built • Including the criteriafor choosing the function of transformation of rating value into the base scale • Comparison of credit ratings has been performed • Models were verified by international bank data and other mapping approaches • The main problems are DATA, MONITORING and VERIFICATION of models Karminsky, Sosyurko, Vasilyuk - Comparison of Bank Credit Ratings Assigned by Rating Agencies EBES 2011 CONFERENCE - ISTANBUL
Q & A Alexander Karminsky, Prof., Dr. AKarminsky@hse.ru karminsky@mail.ru Vladimir Sosyurkovsosyurko@mail.ru Alexander Vasilyuk a.a.vasilyuk@gmail.com Higher School of Economics (HSE) Moscow, Russia Thank you for your attention! Karminsky, Sosyurko, Vasilyuk - Comparison of Bank Credit Ratings Assigned by Rating Agencies EBES 2011 CONFERENCE - ISTANBUL