Managing Director, Head of Stress Testing and Credit Risk Analytics, APAC
David T. Hamilton is a Managing Director in charge of stress testing and credit risk analytics for the Asia Pacific Region, based in Singapore. Dr. Hamilton has been with Moody’s for eighteen years and has held various senior positions in both Moody’s Investors Service and Moody’s Analytics.
David T. Hamilton is a Managing Director in charge of stress testing and credit risk analytics for the Asia Pacific Region, based in Singapore. Dr. Hamilton has been with Moody’s for eighteen years and has held various senior positions in both Moody’s Investors Service and Moody’s Analytics. Over his career with Moody’s, Dr. Hamilton has done research on various aspects of credit risk in a variety of sectors, including corporate, sovereign, municipal, and structured finance.
Prior to joining Moody’s in 1997, Dr. Hamilton worked in the Regional Economics group at the Federal Reserve Bank of Philadelphia. Dr. Hamilton has lectured on credit risk topics at prestigious universities around the world, including Columbia Business School and The International Center for Financial Asset Management and Engineering (FAME) in Lausanne, Switzerland.
Dr. Hamilton is on the editorial board of the Journal of Credit Risk. He holds a B.A. in economics and classical studies from Texas A&M University and a Ph.D. in financial economics from the City University of New York.
Since the global financial crisis, bank stress testing has become an essential part of regulators’ toolkits for monitoring and maintaining financial stability. The impact of a bank’s stress test results can have large implications for its operations, its shareholders, and for the economy at large. Anticipating the results of a formal stress test through simulation can enhance a bank's internal risk management as well as provide strategic business insight.
In this webinar Moody’s Analytics discuss the Marco-economic and credit market conditions likely to affect the future risk of default for Chinese companies; way to measure and manage the default risk of Chinese firms, and strategies for early detection of default risk.
This whitepaper discusses the findings of our simulation exercise to the corporate loan portfolios of Australia's five largest banks.
In this webinar, David Hamilton presents the results of a simulated stress test of the corporate loan portfolios of Australia’s five largest banks (by asset size) conducted by Moody’s Analytics.
In this webinar, Moody’s Analytics combines the techniques of network analysis with the richness of Moody’s CreditEdge™ platform to compute systemic risk measures spanning the last 20 years for five major southeast Asian economies.
EDF9 — the 9th generation of the Moody's Analytics Public Firm EDFTM (Expected Default Frequency) model — expands the frontiers of structural credit risk modeling. EDF metrics are forward-looking probabilities of default, available on a daily basis for 35,000-plus corporate and financial firms. The updated EDF9 model incorporates insights attained by evaluating the behavior of the prior version, EDF8, over the course of the recent financial and sovereign debt crises.
This article looks back at the Asian financial crisis of 1997-1998 and applies new methods of measuring systemic risk and pinpointing weaknesses, which can be used by today’s financial institutions and regulators.
Identifying At-Risk Names in Your Credit Portfolio
Through much of its history Best Buy was considered one of the most successful retail stores in the US. However, since 2010 the electronics retailer has faced business and financial challenges that are placing increasing pressure on its credit quality.
RIM does not have traded bonds or CDS from which to observe credit spreads, and is not rated by Moody's Investors Service. However, Moody's Analytics' public EDF measure effectively captures and quantifies changes in the company's credit risk.
The EDF measure for Shandong Helon Co.'s has signaled a high level of default risk since the time of the financial crisis in 2008. In 2010 its EDF measure began to trend in a range suggesting heightened risk of default, and in June 2011 its EDF jumped from 2.6% to over 7%. Its EDF measure jumped again in April 2012 to over 10%.
Bankia SA's one-year probability of default jumped sharply in May, from 0.45% at the start of the month to 2.24% as of May 24.
Through-the-Cycle EDF™ (TTC EDF) credit measures are one-year probabilities of default that are largely free of the effect of the aggregate credit cycle, primarily reflecting a firm's enduring, long-run credit risk trend. TTC EDF measures are useful in applications in which a stable PD input is desirable, and for which the expected cost of adjusting credit exposures as PD signals change outweighs the expected cost of negative credit events (such as default).
Banks and their EDF™ Measures Now and Through the Credit Crisis: Too High, Too Low, or Just About Right?
Financial institutions, particularly banks, were at the heart of the credit crisis and subsequent recession, and defaulted at unprecedented rates. It will be a long time before names like Lehman Brothers, Bear Stearns, and Northern Rock fade from the memories of investors and risk managers. Not surprisingly, the experience has redoubled interest in finding effective and efficient ways to provide early warning of credit distress for such entities.