Confronting Credit Rating Reform Confronting Credit Rating Reform � A “Public Good” Approach Jin-Chuan DUAN Risk Management Institute National University of Singapore (July 2010)
JC Duan (07/2010) Confronting Credit Rating Reform – A “Public Good” Approach Background • Credit rating agencies have been heavily criticized in the 2008-09 financial crisis. • Credit ratings are: (1) referenced in regulatory frameworks that affect capital requirements; requirements; (2) used in commercial contracts to set collateral requirements; and (3) employed to determine eligibility of debt instruments in, say, pension portfolios.
JC Duan (07/2010) Confronting Credit Rating Reform – A “Public Good” Approach Background (continued) • Because major CRAs are for-profit, they need to keep rating methods proprietary which can hinder methodological developments. • Major CRAs have been reluctant to downgrade a firm in distress (e.g., Enron, Lehman) firm in distress (e.g., Enron, Lehman) • The business model of CRAs is based on the issuer- pay principle. This could lead to moral hazard and rating shopping.
JC Duan (07/2010) Confronting Credit Rating Reform – A “Public Good” Approach Objectives: NUS-RMI’s credit rating initiative sets out to • Advance scientifically sound credit rating methodologies. • Provide alternative, not-for-profit ratings on 1000 or more Asian firms, representative of 12 or more Asian firms, representative of 12 economies. In addition to contributing to the infrastructure of the world financial system, we strive to • Promote NUS-RMI as a global credit risk research center.
JC Duan (07/2010) Confronting Credit Rating Reform – A “Public Good” Approach Conceptual foundation • Credit ratings (sell-side) are really a “public good”. • The current debate on credit ratings focusing on regulatory changes seems to miss this “public good” aspect. • Providing this “public good” not-for-profit seems to • Providing this “public good” not-for-profit seems to be an obvious alternative. • NUS-RMI will advance credit rating methodologies and offer credit ratings on a not-for-profit basis. In short, treating credit ratings as a “public good”.
JC Duan (07/2010) Confronting Credit Rating Reform – A “Public Good” Approach A unique approach • RMI builds the rating research and production infrastructure – a comprehensive data base, and advanced IT system and a team of support staff. • Researchers have been invited from around the world to take part in the rating model development. Being not-for-profit, researchers will be able to keep their IP. not-for-profit, researchers will be able to keep their IP. • Researchers will share the common research infrastructure but compete to get their models adopted for the RMI ratings. • The RMI rating model will remain current, evolutionary and organic, responding to continual suggestions and/or challenges.
JC Duan (07/2010) Confronting Credit Rating Reform – A “Public Good” Approach A unique approach (continued) • We count on voluntary contribution of ideas, skills and time from individuals all over the world, which is much like Wikipedia, a timely amalgamation of the best ideas. • RMI will perform quality control, such as model validation. Hence, our approach is really a selective validation. Hence, our approach is really a selective Wikipedia. • A global call for proposals has been conducted, and the 11 winning research teams plus an RMI internal team are currently working on their different rating models. More teams have expressed interest in joining this undertaking.
JC Duan (07/2010) Confronting Credit Rating Reform – A “Public Good” Approach A unique approach (continued) • RMI maintains the research infrastructure: (1) a comprehensive database of over 20,000 currently listed Asian firms and around 5,000 delisted firms which include over 1,600 defaulted or bankrupt firms since 1990, and (2) both grid and parallel computing capability. computing capability. • RMI provides financial support to those who require it to travel to Singapore to spend an extended period of time for model development.
JC Duan (07/2010) Confronting Credit Rating Reform – A “Public Good” Approach A unique approach (continued) • Being a not-for-profit rating undertaking, the RMI rating methodology will be non-proprietary and completely transparent. • Human judgment is naturally an integral part of any research. Errors may also occur unintentionally in a research process. The selected rating model will be research process. The selected rating model will be independently validated. • Our rating model implementation will be free of ad hoc human judgment, apart from dealing with occasional data errors that are expected from time to time.
JC Duan (07/2010) Confronting Credit Rating Reform – A “Public Good” Approach A unique approach (continued) • There will be no conflicts of interest since we will not be accepting fees or funding from the firms we rate. Neither will we charge users for using the ratings. • The model selection will be based on the commonly accepted scientific principle – statistically superior accepted scientific principle – statistically superior on a common dataset. • Operational factors, such as data availability, frequency of updates and information content of rating results, will also be factored into the selection.
JC Duan (07/2010) Confronting Credit Rating Reform – A “Public Good” Approach Governance • RMI has set up an internal management process to sign off responsibilities in order to ensure data integrity and implementation accuracy. • There is no plan to set up an independent governance committee. Instead, quality assurance relies on millions of eyes watching much like relies on millions of eyes watching much like Wikipedia. • RMI will not apply for any officially sanctioned credit rating agency status. It will remain as a scientific pursuit, advancing rating methodology and offering alternative credit information. No one will be compelled to use the RMI ratings.
JC Duan (07/2010) Confronting Credit Rating Reform – A “Public Good” Approach Coverage Countries/Economies covered in RMI’s database Economy Exchanges Firms* Australia ASX 1875 China SSE, SZSE (A, B, SME & ChiNext) 1905 Hong Kong HKEX, GEM 1372 India India NSE, BSE NSE, BSE 5235 5235 Indonesia IDX 407 Japan TSE, OSE, OSE-Hercules, JASDAQ, NSE, 3821 SSE, FSE Malaysia Bursa Malaysia (Main, ACE) 979 Philippines PSE 252 Singapore SGX (Mainboard, Catalist, Catalist-NS) 775 * Number of listed firms as of S. Korea KRX, KOSDAQ 1849 2010-04-27 Taiwan TWSE, GreTai (Securities, Emerging) 1568 Thailand SET 565
JC Duan (07/2010) Confronting Credit Rating Reform – A “Public Good” Approach Can we do better? • Moody’s, S&P and Fitch are all very large operations. Through their relationships, they have access to proprietary data. • Is it possible for a much smaller-scale operation to do better, with only publicly available data? • Duffie, Saita and Wang (2007) were able to achieve an accuracy ratio for default prediction of 88% in the period 1993-2003 using a purely quantitative model. • This compares favorably to Moody’s accuracy ratio of 65% in the period 1999-2003.
JC Duan (07/2010) Confronting Credit Rating Reform – A “Public Good” Approach Can we do better? (continued) If we could hire Paul, the oracle octopus .....
JC Duan (07/2010) Confronting Credit Rating Reform – A “Public Good” Approach Yes, we can • Duan, Sun and Wang (2010) proposed a forward default intensity approach to generate the term structure of default probabilities. • They demonstrated that the forward default intensity method works well for the US data. We applied it to the RMI database and obtained good applied it to the RMI database and obtained good results. • The beta version of the RMI rating system will be based on the forward default intensity method. • Just like Wikipedia, this credit rating method is meant to be challenged and improved.
JC Duan (07/2010) Confronting Credit Rating Reform – A “Public Good” Approach Yes, we can (continued) Default prediction performance for US (DSW, 2010)
Recommend
More recommend
