Donald R. Van Deventer, Ph.D.

Don founded Kamakura Corporation in April 1990 and currently serves as Co-Chair, Center for Applied Quantitative Finance, Risk Research and Quantitative Solutions at SAS. Don’s focus at SAS is quantitative finance, credit risk, asset and liability management, and portfolio management for the most sophisticated financial services firms in the world.

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A Stress-Testing Case Study: Applying the Fed’s CCAR 2013 Stress Tests to the S&P 500

02/21/2013 12:44 PM

On November 9, 2012, the Federal Reserve announced the details of its Comprehensive Capital Analysis and Review (“CCAR”) Stress Tests 2013. Many institutions responded to the stress test requirements with calculations by each business and risk silo of the organization, with consolidation done after the fact. For many firms, the calculations themselves were spreadsheet-based, rather than being performed on a fully consistent basis using a state of the art enterprise risk management system.  In this blog, we show the ease of stress testing for any stress test scenarios and for any type of portfolio, whether the exposures are sovereign, corporate, small business, retail, or a combination.  In today’s blog, we choose the Federal Reserve CCAR 2013 stress tests as the calculation to be performed.  We assume the portfolio is a set of equal $1,000,000 exposures to each firm in the Standard & Poor’s 500.

Information on the Federal Reserve CCAR 2013 Stress Tests

In the wake of the 2006-2011 credit crisis, many regulators and bankers concluded that the long-time reliance on value-at-risk as a single index of risk was inadequate.  Regulators around the world have imposed specific scenario stress tests as a supplemental measure of exposure to major movements in macro-economic factors.  The Federal Reserve’s stress testing program has two major components:

Summary Instructions and Guidance are available at this link:


Supervisory Scenarios were announced six days later on November 15, 2012:


We now turn to the calculation of the stress tests by Kamakura.

Kamakura Risk Manager and KRIS Credit Portfolio Manager

Kamakura clients have the option of either performing the Fed CCAR stress tests and other stress tests on their own site or via the outsourced Kamakura On-line Processing Service (“KOPS”).  Kamakura Risk Manager, now in version 8.1, is a fully integrated enterprise-wide risk management system.  Kamakura Risk Information Service Credit Portfolio Manager (“KRIS-CPM”) is a software-as-a-service enterprise risk management system that a client can invoke from his web browser.

In today’s blog, we use the KRIS-CPM system to illustrate the ease of stress testing calculations.  The Federal Reserve’s stress test scenarios (and other common sets of stress test macro-economic variables) are already loaded in KRIS-CPM.  There are 26 macro-economic variables that drive risk in the Fed scenarios:

We will briefly review the Fed’s assumptions in the three scenarios in the CCAR stress testing program: the base case, the adverse scenario, and the severe scenario.  We review the scenarios for macro factors that were at the heart of the high default rates in the 2006 to 2011 credit crisis.

Home prices

The Fed scenarios assume a gradual home price recovery in the base case and declines of increasing magnitude in the adverse and severe scenarios:

Unemployment Rate

Similarly, the Fed’s base case assumes a gradual improvement in the unemployment rate, but further increases are projected in the adverse and severe scenarios.

Dow Jones Stock Index Levels

The Fed’s base case assumes a steady rise in the Dow Jones Index, while the adverse and severe scenarios call for a decline and delayed recovery in the index:

Volatility Levels

All three scenarios project a rise and then fall in the S&P volatility index, the VIX, but the severe scenario projects a rise in the VIX to very high levels.

Case Studies in the Response of Default Probabilities to Stress Tests

The heart of the stress testing exercise, both for the Fed and for internal risk management purposes, is the response of the credit spreads and default probabilities for all counterparties, from retail to sovereigns, to changes in the macro-factor scenarios. KRIS-CPM and KRM contain a library of recently updated econometric relationships that link default probabilities of every public firm (and other types of reference names) to specific sets of macro factors, one of which is the Fed’s CCAR 2013 macro factors.  In this section, we look informally at a selection of firms in our assumed S&P 500 portfolio.  We want to analyze the impact of the three Fed scenarios on the default probabilities of each of these firms.

Amazon.com Inc.

Amazon default probabilities deteriorate as one would expect in the adverse and severe scenarios, but they quickly recover by the end of the stress test period:

American Express Company

American Express default probabilities show a high degree of resistance to the impact of deteriorating macro-economic conditions.  They have a low sensitivity to the state of the economy.

American International Group

After the rescue of AIG by the U.S. government, the re-constituted AIG does still show a moderate degree of default probability response to the Fed scenarios, but recovery is strong as the projected business cycle improves.

Bank of New York Mellon

Bank of New York Mellon also shows a surge in default risk in response to the severe scenario, but the adverse scenario has a relatively minor impact on default risk.

Berkshire Hathaway

Berkshire Hathaway shows almost no response to a change in economic scenarios. Default probabilities are quite low in all three scenarios.

Goldman Sachs

Goldman Sachs default probabilities rise to approximately one percent in the severe scenario, one of the strongest performances among major financial institutions.

Huntington Bancshares

Huntington Bancshares default probabilities rise in a fashion more typical of major financial institutions. Under the Fed’s severe scenario, default probabilities break the 10 percent level.


MetLife default probabilities show less of a response to the Fed’s severe scenario than Huntington Bancshares, but the impact is still a significant one.

McDonald’s Corporation

The default probabilities for McDonald’s Corporation are much less cyclical than most major banks, proving there’s less risk in burgers than banks.

Oracle Corporation

Oracle default probabilities do move in the adverse and severe scenarios, but in no case do they exceed one percent. Again, Oracle shows much less default risk cyclicality than major financial institutions.

Wal-mart Stores Inc.

Wal-mart is another firm whose default probabilities show only very modest sensitivity to the Fed scenarios, barely exceeding the 0.10% level in the severe scenario.

We now turn to the aggregate portfolio losses that result from an equal-weighted exposure ($1 million exposure to each firm) of the S&P 500 portfolio.

Results of the CCAR 2013 Stress Tests

KRIS-CPM and Kamakura Risk Manager use the stress test scenarios to project the macro-economic factors in each period and derive the default probabilities that will prevail for all 500 names in the portfolio (a) at each point in time and (b) in each Fed scenario.  For each of the 3 Fed “macro scenarios,” we simulate a large number of sub-scenarios, say n. In scenario k, we simulate default/no default for all 500 names given at period 1 (quarter number 1).  In scenario k, say there are 10 defaulters.  When we move to period 2 in scenario k, default probabilities will be generated for the 490 survivors.  If 15 more firms default, the surviving 475 firms will be simulated, and so on.  We do this analysis through the 13 quarters of the Fed stress test and we repeat n times, for each of the 3 Fed “macro scenarios.”

KRIS-CPM and KRM both report, among other outputs, the median cumulative credit losses at each point in time over all n scenarios for each of the three Fed macro scenarios.  The chart below shows that credit losses are modest in the base case scenario, less than $5 million on a portfolio with an original notional value of $500 million.  In the adverse scenario, cumulative losses reach approximately $35 million by the end of the 13th quarter.  In the severe scenario, losses total $65 million.  For simplicity’s sake, we have assumed a loss given default equal to 100% of notional exposure. Cumulative losses would be proportionately smaller at a lower loss given default.

This example shows that a modern software-as-a-service enterprise risk system like KRIS-CPM or Kamakura Risk Manager, via KOPS, has a number of advantages:

Totally consistent stress test analysis across all types of counterparties
Totally consistent stress test analysis across all business units
Consistent linkage between macro-factors and modern default probabilities
Best practice quantitative default probabilities with an explicit maturity (unlike ratings), updated daily (unlike ratings, which on average have not been adjusted for 2 years and 3 months for the median rated public firm)
Fully transparent and disclosed analysis
Widely vetted and widely used by the world’s most sophisticated financial institutions and regulators.

For more on this approach, please contact us at Info@KamakuraCo.com.

Donald R. van Deventer
Kamakura Corporation
Honolulu, Hawaii
February 21, 2013

Copyright © 2013 by Donald R. van Deventer. All Rights Reserved.
Background Information on the Kamakura CCAR 2013 Stress Testing Service
The Kamakura CCAR 2013 Stress Testing Service is conducted using two powerful Kamakura risk management systems: the Kamakura Risk Manager Version 8.1 enterprise risk system and the KRIS Credit Portfolio Manager software-as-a-service solution.  Both KRM and KRIS-CPM take advantage of Kamakura’s extensive KRIS default probability service which links the default probabilities of 31,000 public firms, non-public firms, retail borrowers and sovereigns to the 26 CCAR stress testing variables announced by the Federal Reserve in November 2012.

Martin Zorn, Chief Administrative Officer for Kamakura Corporation, commented, “For many financial institutions, the CCAR stress testing process has meant the amalgamation of hundreds of spreadsheets and disparate, inconsistent risk systems that vary by business unit and bank location.  The Kamakura CCAR Stress Testing Service provides a fully automated stress testing capability at the transaction level that is accurate and consistent across all risk ‘silos’ and business units. It is the fully automated nature of the Kamakura infrastructure that allows Kamakura to begin processing for clients only two business days after the announcement of the Fed’s stress test scenarios for 2013.”

Kamakura’s general outsourced processing service Kamakura On-Line Processing Service (“KOPS”) allows financial institutions of all locations and sizes to outsource risk management calculations of all types, not just the Federal Reserve’s CCAR stress test scenarios. Kamakura KOPS clients have used the KOPS analysis for many purposes: as a primary measure of risk, as a third party “audit” of an in-house risk system, as a valuation service for the accounting for complex “Level 3” securities, and for top priority merger and acquisition analysis.  For more on the Kamakura On-Line Processing Service, please see



Donald R. Van Deventer, Ph.D.

Don founded Kamakura Corporation in April 1990 and currently serves as Co-Chair, Center for Applied Quantitative Finance, Risk Research and Quantitative Solutions at SAS. Don’s focus at SAS is quantitative finance, credit risk, asset and liability management, and portfolio management for the most sophisticated financial services firms in the world.

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