Moody’s Analytics Launches Through-the-Cycle Probability of Default Measure
New credit risk measure to address needs of institutions dealing with regulatory capital requirements
Moody’s Analytics, a leader in credit risk measurement and management, today announced Through-the-Cycle EDF™ (Expected Default Frequency) measure, a quantitatively derived credit risk estimate that dampens the short-term volatility arising from the aggregate credit cycle, providing more stable default probabilities than traditional point-in-time (PIT) credit risk estimates.
Through-the-Cycle EDF measures have been developed for applications in which a stable default probability input is desirable, such as banks and similar financial institutions managing regulatory capital requirements and long-term portfolio investment mandates.
“Credit analysts have long struggled to manage the tension between default prediction accuracy and stability in their measurement of credit risk,” said David Hamilton, managing director of Quantitative Credit Research at Moody’s Analytics. “While point-in-time default measures are powerful predictors because they capture all available information, they are highly volatile and can obscure long-term credit quality signals. Through-the-Cycle EDFs preserve much of the accuracy of traditional point-in-time EDF measures, while eliminating noise from market-wide movements, yielding a superior balance of prediction accuracy and stability.”
Covering more than 30,000 companies globally, Through-the-Cycle EDFs are derived from Moody’s Analytics’ public firm EDF model, the industry-leading structural credit risk model. Moody’s Analytics research shows that Through-the-Cycle EDFs reduce cyclical volatility by 50% or more for the vast majority of companies.
TTC-EDFs are particularly relevant for risk management applications where frequently adjusting credit exposures imposes high portfolio management costs. Changing capital reserves can be costly and disruptive for banks and other managers of credit portfolios. In such cases, institutions seek to avoid making changes to capital reserves and/or portfolio exposures in response to volatility attributable to short-term, market-wide fluctuations.
Through-the-Cycle EDFs complement Moody’s Analytics’ traditional EDF, a point-in-time metric that estimates a firm’s probability of default using information from equity markets, company financial statements, and capital structure. The sensitivity of the traditional EDF metric makes it a reliable early-warning indicator of credit risk, and as such can be used together with the Through-the-Cycle EDF measure for a comprehensive perspective on single-name and portfolio-level credit quality.
“A complete credit risk management system requires both point-in-time and through-the-cycle probabilities of default,” said Hamilton. “A single default probability measure is insufficient to address the diverse credit risk and portfolio management needs faced by banks and other institutions. Moody’s Analytics now provides a range of risk measures, linked by a consistent, transparent methodology.”
Through-the-Cycle EDF measures join a series of recent innovations from Moody’s Analytics, including Sovereign EDF credit metrics and CDS-Implied EDF credit metrics.
