Global Credit Review - Volume 4

Volume 4

Risk Management Institute

• Publisher: WSPC
• Year: 2014
• eBook ISBN: 9789814635493
• Topic: Biological Sciences
• Subtopic: Science General
• Index: Biological Sciences

Global Credit Review is an annual publication that provides an overview of the most important developments in global credit markets and the regulatory landscape. The fourth volume covers theoretical and empirical research on credit ratings and credit risk, and reports on recent findings and evolutions of the RMI Credit Research Initiative. The ultimate objective of this publication is to advance the state of research and development in the critical area of credit risk and rating systems. With a distinctive focus on topics related to credit markets and credit risk, this publication will be of interest to finance professionals, policy makers and academics with an interest in credit markets.

Contents:

• Message from the Editor
• An Assessment of Systemic Risk in the Japanese Banking Sector (Masayasu Kanno)
• Evolving Global Capital Regulations and its Impact Particularly on Asia (Dexter Tan & Thomas Cho)
• Actuarial Par Spread and Empirical Pricing of CDS by Decomposition (Jin-Chuan Duan)
• Fast Approximation of Loan Portfolio Loss (Jenny Bai, Heikki Seppälä and Ser-Huang Poon)
• Rejection and Partial Rejection of Consumer Credit Applications (Steven E Plaut)
• IACPM/Oliver Wyman Survey: Perspectives on the Evolving Role of Enterprise-Wide Stress Testing (Andy McGee & Ilya Khaykin)
• NUS-RMI Credit Research Initiative Technical Report Version: 2014 Update 1 (RMI staff article)

Readership: Finance professionals, policy makers and academics with an interest in credit markets.

NUS-RMI Credit Research Initiative Technical Report Version: 2014 Update 1

RMI staff article

For any questions or comments on this article, please contact the CRI-team at [email protected]

Keywords: Non-profit credit research initiative, credit risk, probability of default, forward intensity.

This document describes the implementation of the system which the Credit Research Initiative (CRI) at the Risk Management Institute (RMI) of the National University of Singapore (NUS) uses to produce probabilities of default (PDs). As of this version of the Technical Report, RMI covers around 60,400 listed firms (including delisted ones) in 106 economies around the world (see Table A.1). Of the around 40,000 active firms under the CRI coverage, around 34,000 firms have sufficient data to release daily updated PDs. The PD for all firms is freely available to users who can provide evidence of their professional qualifications to ensure that they will not misuse the data. General users who do not request global access are restricted to a list of 3,000 firms. The individual company PD data, along with aggregate PDs at the economy and sector level, can be accessed at http://rmicri.org.

The primary goal of this initiative is to drive research and development in the critical area of credit rating systems. As such, a transparent methodology is essential to this initiative. Having the details of the methodology available to everybody means that there is a base from which suggestions and improvements can be made. The objective of this Technical Report is to provide a full exposition of the CRI system. Readers of this document who have access to the necessary data and who have a sufficient level of technical expertise will be able to implement a similar system on their own. For a full exposition of the conceptual framework of the CRI, see Duan and Van Laere (2012).

The system used by the CRI will evolve as new innovations and enhancements are applied. The changes to the 2013 technical report and operational implementation of our model are: (1) the changes in financial statement (FS) priority rules for Australia, South-Korea and Taiwan; (2) the changes to the winsorization for market-to-book ratio; (3) some changes to the monthly calibration for the Emerging Markets Group; (4) a reclassification of default events in Thailand; (5) a replacement for the stock index in Jordan; (6) replacements for the 3-month interest rates in Russia and Singapore; (7) a replacement for the riskfree rate in Sweden; and (8) revision to balance sheet items used in distance-to-default (DTD). This version of the technical report provides an update on the operational implementation of the CRI and includes all changes to the system that had been implemented by March 2014. More specifically, in addition to Technical Report version: 2013 update 2, the current version of the technical report specifies some revisions to the monthly parameter updates that went into effect as of the April 2014 calibration. The latest version of the Technical Report and addenda to the latest version are available via the web portal and will include any changes to the system that have been implemented since the publication of this version.

The remainder of this Technical Report is organized as follows. The next section describes the quantitative model that is currently used to compute PDs from the CRI. The model was first described in Duan et al. (2012). The description includes calibration procedures, which are performed on a monthly basis, and individual firm PD computations, which are performed on a daily basis.

Section II describes the input variables of the model as well as the data used to produce the variables for input into the model. This model uses both input variables that are common to all firms in an economy and input variables that are firm-specific. Another critical component when calibrating a probability of default estimation system is the default data, and this is also described in this section.

While Section I provides a broader description of the model, Section III describes the implementation details that are necessary for application, given real world issues of, for example, bad or missing data. The specific technical details needed to develop an operational system are also given, including details on the monthly calibration, daily computation of individual firm PDs and aggregation of the individual firm PDs. DTD in a Merton-type model is one of the firm-specific variables. The calculation for DTD is not the standard one, and has been modified to allow a meaningful computation of the DTD for financial firms. While most academic studies on default prediction exclude financial firms from consideration, it is important to include them given that the financial sector is a critical component in every economy. The calculation for DTD is detailed in this section.

Section IV shows an empirical analysis for those economies that are currently covered. While the analysis shows excellent results in several economies, there is room for improvement in a few others. This is because, at the CRI’s current stage of development, the economies all use the variables used in the academic study of US firms in Duan et al. (2012). Future development within the CRI will deal with variable selection specific to different economies, and the performance is then expected to improve. Other planned developments are discussed in Sec. V.

I. MODEL DESCRIPTION

The quantitative model that is currently being used by the CRI is a forward intensity model that was introduced in Duan et al. (2012). Certain aspects of the model are taken from Duan and Fulop (2013). This model allows PD forecasts to be made at a range of horizons. In the current CRI implementation of this model, PDs are forecasted from a horizon of one month up to a horizon of five years. At the RMI CRI website, for every firm, the probability of that firm defaulting within one month, three months, six months, one year, two years, three years and five years is given. The ability to assess credit quality for different horizons is a useful tool for risk management, credit portfolio management, policy setting and regulatory purposes, since short- and longterm credit risk profiles can differ greatly depending on a firm’s liquidity, debt structures and other factors.

The forward intensity model is a reduced form model i...

Table of contents

• Book Cover
• Title Page
• Copyright
• Message from the Editor
• Contents
• An Assessment of Systemic Risk in the Japanese Banking Sector
• Evolving Global Capital Regulations and Its Impact Particularly on Asia
• Actuarial Par Spread and Empirical Pricing of CDS by Decomposition
• Fast Approximation of Loan Portfolio Loss
• Rejection and Partial Rejection of Consumer Credit Applications
• IACPM/Oliver Wyman Survey: Perspectives on the Evolving Role of Enterprise-Wide Stress Testing
• NUS-RMI Credit Research Initiative Technical Report Version: 2014 Update 1