Method and system for predicting credit ratings transitions

• US 7,761,373 B2
• Filed: 04/30/2008
• Issued: 07/20/2010
• Est. Priority Date: 04/30/2008
• Status: Active Grant

• Current Assignee: Moody's Investors Service Incorporated (Moody's Corporation)
• Original Assignee: Moody's Investors Service Incorporated (Moody's Corporation)
• Inventors: Metz, Albert Diederich
• Primary Examiner(s): Abdi; Kambiz
• Assistant Examiner(s): MARCUS, LELAND R
• Application Number:
  US12/149,318
• Publication Number:
  US 20090276234A1
• Time in Patent Office: 811 Days
• Field of Search: 705/38, 705/35
• US Class Current: 705/38
• CPC Class Codes: G06Q 40/00 Finance; Insurance; Tax strategies; Processing of corporate or income taxes
• CPC Class Codes: G06Q 40/02 Banking, e.g. interest calculation or account maintenance credit or loans G06Q40/03
• CPC Class Codes: G06Q 40/03 Credit; Loans; Processing thereof
• CPC Class Codes: G06Q 40/04 Trading; Exchange, e.g. stocks, commodities, derivatives or currency exchange

Abstract

A system and method is provided for allowing users to create portfolios of issuers and macroeconomic scenarios used to determine pertinent rating facts and future paths of macroeconomic drivers. The system and method use the pertinent rating facts and the future paths of macroeconomic drivers, namely unemployment rates and high yield spreads, as inputs to a Credit Transition Model (CTM). The system and method generate a complete set of rating transitions, including predicting the probability of default, while taking into account withdrawal of issuers to more accurately reflect default rates. The system and method provide users with multiple choices for outputs from the CTM and can easily and quickly generate results from the model.

Claims

1. A method, comprising:

accessing rating facts about one or more issuers using a computer processor;

receiving information about one or more future paths for a first macroeconomic factor and one or more future paths for a second macroeconomic factor by the computer processor, wherein the first macroeconomic factor is an unemployment rate and the second macroeconomic factor is a high yield spread;

calculating, using the computer processor, one or more probabilities of credit rating transitions between credit rating states for the one or more issuers over a time period by a credit transition model based on the rating facts about the one or more issuers, the one or more future paths for the first macroeconomic factor, and the one or more future paths for the second macroeconomic factor, wherein the credit transition model includes a credit rating state of withdrawal from rating; and

generating outputs from the computer processor based on the one or more probabilities of credit rating transitions from the credit transition model, wherein the outputs are capable of being displayed using a computer system with display.

2. The method of claim 1, wherein the rating facts comprise one or more of the following:

a current rating, a rating momentum, a rating history, an outlook status, and a watchlist status.

3. The method of claim 1, wherein the step of calculating one or more probabilities of credit rating transitions further comprises performing an adjustment for withdrawal of the one or more issuers from rating.

4. The method of claim 1, wherein the step of generating outputs further comprises performing an adjustment for withdrawal of the one or more issuers from rating.

5. The method of claim 1, wherein the outputs generated from the credit transition model comprise one or more of the following at the issuer level or at a portfolio level:

rating migration matrices, marginal default rates, cumulative default rates, first passage probabilities, default distributions, fallen angel rates, rising star rates, forecasted ratings, drill-through reports, and summary reports.

6. A method, comprising:

receiving with a computer processor one or more portfolios including information about one or more issuers;

receiving with the computer processor one or more macroeconomic scenarios including information about a first macroeconomic factor and receiving one or more macroeconomic scenarios including information about a second macroeconomic factor, wherein the first macroeconomic factor is an unemployment rate and the second macroeconomic factor is a high yield spread;

determining, using the computer processor, rating facts about the one or more issuers based on the one or more portfolios;

receiving with the computer processor information about one or more future paths for the first macroeconomic factor and one or more future paths for the second macroeconomic factor based on the received one or more macroeconomic scenarios;

applying, using the computer processor, a credit transition model using the rating facts about the one or more issuers, the one or more future paths for the first macroeconomic factor, and the one or more future paths for the second macroeconomic factor by the computer processor;

calculating, using the computer processor, one or more probabilities of credit rating transitions between credit rating states for the one or more issuers over a time period by the credit transition model based on the rating facts about the one or more issuers, the one or more future paths for the first macroeconomic factor, and the one or more future paths for the second macroeconomic factor, wherein the credit transition model includes a credit rating state for withdrawal from rating; and

generating outputs from the computer processor based on the one or more probabilities of credit rating transitions from the credit transition model, wherein the outputs are capable of being displayed using a computer system with display.

7. The method of claim 6, wherein the step of receiving one or more portfolios further comprises receiving criteria for determining the one or more issuers.

8. The method of claim 7, wherein the criteria comprise one or more of the following:

one or more issuers to include, one or more issuers to exclude, one or more regions, one or more industries, and one or more ratings categories.

9. The method of claim 6, wherein the rating facts comprise one or more of the following:

a current rating, a rating momentum, a rating history, an outlook status, and a watchlist status.

10. The method of claim 9, wherein the step of receiving one or more portfolios further comprises receiving weights for each of the one or more issuers.

11. The method of claim 10, wherein the weights are volume weighted or dollar weighted.

12. The method of claim 6, wherein the step of receiving one or more macroeconomic scenarios further comprises receiving a selection of one or more information sources for the one or more macroeconomic scenarios.

13. The method of claim 12, wherein the one or more information sources includes a historical scenario, a custom scenario, and a scenario from a predetermined source.

14. The method of claim 13, wherein the custom scenario is created by a user.

15. The method of claim 13, wherein the scenario from a predetermined source is based on an output from an economic forecasting model.

16. The method of claim 13, wherein the scenario from a predetermined source includes a baseline scenario, scenario having an economic upside, or a scenario having an economic downside.

17. The method of claim 6, further comprising the step of receiving a withdrawal adjustment, wherein the withdrawal adjustment comprises one or more of the following:

a sophisticated adjustment, an adjustment for historical comparison, and a custom adjustment with a reinvestment assumption.

18. The method of claim 6, wherein the step of applying the credit transition model further comprises performing an adjustment for withdrawal of the one or more issuers.

19. The method of claim 6, wherein the step of applying a credit transition model further comprises:

(i) calling a plurality of credit transition model parameters by the computer processor; and

(ii) applying the credit transition model using the plurality of credit transition model parameters.

20. The method of claim 6, wherein the outputs generated from the credit transition model comprise one or more of the following at the issuer or portfolio level:

rating migration matrices, marginal default rates, cumulative default rates, first passage probabilities, default distributions, fallen angel rates, rising star rates, forecasted ratings, drill-through reports and summary reports.

21. The method of claim 6, wherein the step of generating outputs further comprises performing an adjustment for withdrawal of the one or more issuers.

22. The method of claim 6, further comprising the step of transmitting the outputs from the credit transition model from the computer processor to a communication terminal.

23. A system, comprising:

a computer, the computer including a portfolio module, a scenario module, a statistical modeling module, and an output module;

the portfolio module configured to receive one or more portfolios comprising information about one or more issuers;

the scenario module configured to receive one or more macroeconomic scenarios including information about a first macroeconomic factor and receiving one or more macroeconomic scenarios including information about a second macroeconomic factor, wherein the first macroeconomic factor is an unemployment rate and the second macroeconomic factor is a high yield spread;

the statistical modeling module configured to determine rating facts about the one or more issuers based on the one or more portfolios, receive information about one or more future paths for the first macroeconomic factor and one or more future paths for the second macroeconomic factor, apply a credit transition model using the rating facts about the one or more issuers, the one or more future paths for the first macroeconomic factor, and the one or more future paths for the second macroeconomic factor; and

calculate one or more probabilities of credit rating transitions between credit rating states of the one or more issuers over a time period by the credit transition model based on the rating facts about the one or more issuers, the one or more future paths for the first macroeconomic factor, and the one or more future paths for the second macroeconomic factor, wherein the credit transition model includes a credit rating state for withdrawal from rating; and

the output module configured to generate outputs based on the one or more probabilities of credit rating transitions from the credit transition model, wherein the outputs are capable of being displayed using a computer system with display.

24. A method, comprising:

displaying, using a computer, a portfolio interface for inputting issuer information of issuers;

displaying, using the computer, a macroeconomic scenario interface for inputting information about unemployment rates and information about high yield spreads;

transmitting from the computer the issuer information, the information about unemployment rates, and the information about high yield spreads to a credit transition model for generating probabilities of credit rating transitions between credit rating states for the issuers over a period of time, the credit transition model including a credit rating state for withdrawal from rating, wherein the credit transition model generates the probabilities of credit rating transitions using the issuer information, the information about unemployment rates, and the information about high yield spreads;

receiving by the computer one or more probabilities of credit rating transitions generated from the credit transition model; and

displaying, using the computer, outputs of the one or more probabilities of credit rating transitions on the graphical user interface.

25. The method of claim 24, wherein the outputs generated from the credit transition model comprise one or more of the following at the issuer or portfolio level:

rating migration matrices, marginal default rates, cumulative default rates, first passage probabilities, default distributions, fallen angel rates, rising star rates, forecasted ratings, drill-through reports and summary reports.

26. A system, comprising:

a communication terminal, the communication terminal configured (a) to transmit information about one or more issuers, unemployment rates, and high yield spreads to a credit transition model for generating probabilities of credit rating transitions between credit rating states of the issuers over a period of time, the credit transition model including a credit rating state for withdrawal from rating, and (b) to receive one or more probabilities of credit rating transitions generated from the credit transition model, the credit transition model predicting the one or more probabilities using the information about one or more issuers, unemployment rates, and high yield spreads; and

a graphical user interface to display the one or more probabilities of credit rating transitions.