Alexander Karminsky Vladimir Sosyurko Alexander Vasilyuk National Research University Higher School...

Alexander KarminskyVladimir SosyurkoAlexander Vasilyuk

National Research University “Higher School of Economics”

Moscow, Russia

Comparison of Bank Credit Ratings Assigned by Rating Agencies

EBES 2011 CONFERENCE - ISTANBULJune, 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 2

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

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.

Rating agencies in Russia



596 ratings at the end of 2010

Number of bank ratings259 358 454 604 596

2006 2007 2008 2009 2010

7 agencies = 3 international & 4 national

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



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

RatingScales

NumericScales

RS1

RSi

RSN

NS1

NSi

NSN

BS

F1(α1)

Fi(αi)

FN(αN)

Base Scale

*iy

Rating modeling (Ordered probit models)



,*iii xy 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

).(1)(

,12),()()(

),()0(

1

1

1

iki

irtri

ii

xcFkyP

krxcFxcFryP

xcFyP

,

,12,

,1

1*

*1

1*

kii

riri

ii

cyifky

krcycifry

cyify

Research data

10 rating scales: 4 national rating agencies 3 international agencies (3+3)

Time period: 1q2006 – 4q2010 (20 quarters)

370 Russian banks with at least 1 rating during this period

Total 7400 observations of banks



Numerical scales



S&P S&P (rus) Moody’sMoody’s

(rus)Fitch Fitch (rus) Expert RA NRA АК&М Rus-Rating

SP SP_ru M M_ru F F_ru ERA NRA AKM RRAAA 1 ruAAA 1 Aaa 1 Aaa.ru 1 AAA 1 AAA(rus) 1 A++ 1 AAA 1 A++ 1 AAA 1

AA+ 2 ruAA+ 2 Aa1 2 Aa1.ru 2 AA+ 2 AA+(rus) 2 A+ 2 AA+ 2 A+ 2 AA+ 2AA 3 ruAA 3 Aa2 3 Aa2.ru 3 AA 3 AA(rus) 3 A 3 AA 3 A 3 AA 3AA- 4 ruAA- 4 Aa3 4 Aa3.ru 4 AA- 4 AA-(rus) 4 B++ 4 AA- 4 B++ 4 AA- 4A+ 5 ruA+ 5 A1 5 A1.ru 5 A+ 5 A+(rus) 5 B+ 5 A+ 5 B+ 5 A+ 5A 6 ruA 6 A2 6 A2.ru 6 A 6 A(rus) 6 B 6 A 6 B 6 A 6A- 7 ruA- 7 A3 7 A3.ru 7 A- 7 A-(rus) 7 C++ 7 A- 7 C++ 7 A- 7BBB+ 8 ruBBB+ 8 Baa1 8 Baa1.ru 8 BBB+ 8 BBB+(rus) 8 C+ 8 BBB+ 8 C+ 8 BBB+ 8

BBB 9 ruBBB 9 Baa2 9 Baa2.ru 9 BBB 9 BBB(rus) 9 C 9 BBB 9 C 9 BBB 9

BBB- 10 ruBBB- 10 Baa3 10 Baa3.ru 10 BBB- 10 BBB-(rus) 10 BBB- 10 BBB- 10BB+ 11 ruBB+ 11 Ba1 11 Ba1.ru 11 BB+ 11 BB+(rus) 11 BB+ 11 BB+ 11BB 12 ruBB 12 Ba2 12 Ba2.ru 12 BB 12 BB(rus) 12 BB 12 BB 12BB- 13 ruBB- 13 Ba3 13 Ba3.ru 13 BB- 13 BB-(rus) 13 BB- 13 BB- 13B+ 14 ruB+ 14 B1 14 B1.ru 14 B+ 14 B+(rus) 14 B+ 14B 15 ruB 15 B2 15 B2.ru 15 B 15 B(rus) 15 B 15B- 16 ruB- 16 B3 16 B3.ru 16 B- 16 B-(rus) 16 B- 16

CCC+ 17 ruCCC+ 17 Caa1 17 Caa1.ru 17 CCC+ 17CCC+(rus)

17 CCC+ 17

CCC 18 ruCCC 18 Caa2 18 Caa2.ru 18 CCC 18 CCC(rus) 18 CCC 18

CCC- 19 ruCCC- 19 Caa3 19 Caa3.ru 19 CCC- 19 CCC-(rus) 19 CCC- 19CC 20 ruC 20 C 20 C.ru 20 C 20 C(rus) 20 C 20

Criteria for choosing the mapping function



Q – set of all observations {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

Qijtiiijtii

NiRFRF

i

2222111

},..,1,{)),(),((min

Mapping function

Multiple mapping into the base scale:

linear logarithmic polynomial (up to 5th

power)



Moody’s – Moody’s (rus)

Moody’s – S&P

Logarithmic model of multiple mapping

Moody’s credit ratings (R) and default probabilities (PD) of banks are approximated by a logarithmic dependence during the years 1980-2008



0

5

10

15

20

25

1 3 5 7 9 11 13 15 17 19

PD = 0,000218×R3,8

PD(%)

R

M = const∙Ra ↔ Ln(M) = a∙Ln(R)+b

Variable Coefficients a,b pLOG(M_RU)*D_M_RU 0,254 0,000D_M_RU 2,202 0,000LOG(SP)*D_SP 0,916 0,000D_SP 0,146 0,029LOG(SP_RU)*D_SP_RU 0,265 0,000D_SP_RU 2,113 0,000LOG(F)*D_F 0,749 0,000D_F 0,594 0,000LOG(F_RU)*D_F_RU 0,213 0,000D_F_RU 2,162 0,000LOG(AKM)*D_AKM 0,269 0,000D_AKM 2,491 0,000LOG(ERA)*D_ERA 0,373 0,000D_ERA 2,329 0,000LOG(RR)*D_RR 0,674 0,000D_RR 1,016 0,000LOG(NRA)*D_NRA 0,163 0,000D_NRA 2,474 0,000Number of Observations 3432 R2 0,902

Logarithmic model for 2006-2010 years:

Rating comparison (logarithmic scales)



Moody’s

S&P

Fitch

Fitch (rus)

Moody’s (rus)

S&P (rus)

Rus-Rating

Expert RA

AK&M

NRA

Comparison of international banks

3639 pairs (Moody’s – another agency) Bank data 1995 – 2010 290 different banks



Moody’s

S&P

Fitch

Credit rating’ comparison for scales of international agencies(logarithmic model)

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 criteria for 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



Q & A

Alexander Karminsky, Prof., Dr. [email protected]

[email protected] Sosyurko

[email protected] Alexander Vasilyuk [email protected]

Higher School of Economics (HSE)Moscow, Russia

Thank you for your attention!



Alexander Karminsky Vladimir Sosyurko Alexander Vasilyuk National Research University Higher School...

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