In this paper, we study how earnings volatility induced by credit risk can impact share price performance for financial institutions under CECL and IFRS 9, and we quantify the benefit of an active credit risk management practice. Our study uses empirical data to show that a 1.0% increase in earnings volatility leads to a 15.6 bps decrease in equity value. When we look at the earnings volatility components, we find that a 1.0% increase in the volatility of change in the loss allowance leads to a 6.0% bps decrease in equity value, while a 1.0% increase in the volatility of net charge-offs plus writedowns leads to a 10.5 bps decrease in equity value. This finding suggests that credit risk managers who diversify holdings and reduce earnings volatility without lowering profitability can increase shareholder value.
Moody's Analytics is pleased to announce the release of versions 5.3 and 5.4 of the RiskFrontier software. The latest version includes the following enhancements:
In 2017's final quarter, the 7.7% yearly advance by nonfinancial-corporate profits from current production outran the accompanying 6.6% increase of nonfinancial-corporate debt. The record shows that if pretax operating profits continue to outpace corporate debt, corporate credit quality will improve. The correlation between the high-yield default rate's quarter-long average and the yearlong ratio of debt-tooperating profits for US nonfinancial corporations is a meaningful 0.82.
John Lonski, Franklin Kim, Yukyung Choi, Ryan Sweet, Kathryn Asher, Michael Ferlez, Thomas Nichols, Barbara Teixeira Araujo, Katrina Ell
Credit portfolio models rely on estimated and calibrated parameters, such as default and rating migration probabilities, recovery rates, and asset correlations. Users of these models must understand how various errors in the parameter estimates impact model outputs, for example Unexpected Loss (UL) or Economic Capital (EC). Asset correlations estimated using asset return time series are subject to inherent uncertainty — statistical errors — arising due to a limited length of the time series. The main question this paper addresses is how these errors translate into statistical errors in the estimated UL and EC. We illustrate several properties of the errors using an analytical method. As expected, longer time series lead to lower errors in UL and EC. Increasing the number of exposures in a portfolio, however, can reduce the errors in UL and EC only to a certain degree.
Jimmy Huang, Libor Pospisil
The Deterioration Probability - At a Glance
The Deterioration Probability Methodology
Partly as a means of offsetting the loss of business activity to deleveraging by households, businesses, as well as state and local governments, the federal government's share of the U.S.' broadest estimate of public and private nonfinancial-sector debt has soared from year-end 2007's 18% to the 34% of 2017's third quarter. The latter share is the highest since 1960's third quarter.
John Lonski, Njundu Sanneh, Franklin Kim, Yukyung Choi, Ryan Sweet, Barbara Teixeira Araujo, Reka Sulyok, Katrina Ell, Faraz Syed
In this webinar, Mark Zandi and the Moody's Analytics team discuss the impact of the wealth effect on economic expansion and quantify econometric estimates based on data from Visa and Equifax.
Auto lending is following a natural and expected credit cycle. Subprime performance will get better as credit tightens. Nonbank auto financiers are facing the highest loss rates when lending to low-income, subprime borrowers. Residual value pressures should begin to abate but will likely increase for trucks and SUVs.
We construct and examine new origination of C&I loans to middle-market borrowers using the Loan Accounting System data extracted from Moody's Analytics Credit Research Database (CRD/LAS). We find that C&I loan origination declines during the Great Recession and recovers soon after. The magnitude of the decline and the speed of the recovery varies across segments. For example, new lending to the financial industry decreases more than to the non-financial industry during the recession and recovers faster afterwards. Another example, new originations during the recession consists predominantly of short-term loans, while long-term lending becomes more dominant post crisis. This finding suggests that banks are using loan tenor as a means to mitigate risk during crises, at times even more so than credit quality.
Dr. Pierre Xu, Tomer Yahalom, May Jeng
Many financial institutions prefer to take longer-term views when assessing the risks of their credit portfolio. While forward-looking or Point-in-Time (PIT) parameters might be more reflective of the current economic environment, frequent updates may create fluctuations in risk measures.
This document presents a credit portfolio stress testing method that analytically determines multi-period expected losses under various macroeconomic scenarios. The methodology utilizes Moody's Analytics Global Correlation Model (GCorr) Macro model within the credit portfolio modeling framework. GCorr Macro links the systematic credit factors from GCorr to observable macroeconomic variables. We describe the stress testing calculations and estimation of GCorr Macro parameters and present several validation exercises for portfolios from various regions of the world and of various asset classes.
Noelle Hong, Jimmy Huang, Albert Lee, Dr. Amnon Levy, Marc Mitrovic, Libor Pospisil, Olcay Ozkanoglu