Stress Testing - Financial Sector

Financial Sector

Instead of doing financial projection on a "best estimate" basis, a company or its regulators may do stress testing where they look at how robust a financial instrument is in certain crashes, a form of scenario analysis. They may test the instrument under, for example, the following stresses:

• What happens if equity markets crash by more than x% this year?
• What happens if GDP falls by z% in a given year?
• What happens if interest rates go up by at least y%?
• What if half the instruments in the portfolio terminate their contracts in the fifth year?
• What happens if oil prices rise by 200%?

This type of analysis has become increasingly widespread, and has been taken up by various governmental bodies (such as the FSA in the UK) or inter-governmental bodies such as the European Banking Authority and the International Monetary Fund) as a regulatory requirement on certain financial institutions to ensure adequate capital allocation levels to cover potential losses incurred during extreme, but plausible, events. This emphasis on adequate, risk adjusted determination of capital has been further enhanced by modifications to banking regulations such as Basel II. Stress testing models typically allow not only the testing of individual stressors, but also combinations of different events. There is also usually the ability to test the current exposure to a known historical scenario (such as the Russian debt default in 1998 or 9/11 attacks) to ensure the liquidity of the institution.

Stress testing reveals how well a portfolio is positioned in the event forecasts prove true. Stress testing also lends insight into a portfolio's vulnerabilities. Though extreme events are never certain, studying their performance implications strengthens understanding.

Defining stress tests

Stress testing defines a scenario and uses a specific algorithm to determine the expected impact on a portfolio's return should such a scenario occur. There are three types of scenarios:

• Extreme event: hypothesize the portfolio's return given a catastrophic event, often the recurrence of a historical event. Current positions and risk exposures are combined with the historical factor returns.
• Risk factor shock: shock any factor in the chosen risk model by a user-specified amount. The factor exposures remain unchanged, while the covariance matrix is used to adjust the factor returns based on their correlation with the shocked factor.
• External factor shock: instead of a risk factor, shock any index, macro-economic series (e.g., oil prices, property prices), or custom series (e.g., exchange rates). Using regression analysis, new factor returns are estimated as a result of the shock.

In an exponentially weighted stress test, historical periods more like the defined scenario receive a more significant weighting in the predicted outcome. The defined decay rate lets the tester manipulate the relative importance of the most similar periods. In the standard stress test, each period is equally weighted.

Stress tests in payment and settlement systems

Another form of financial stress testing is the stress testing of financial infrastructure. As part of Central Banks' market infrastructure oversight functions, stress tests have been applied to payment and securities settlement systems. Since ultimately, the Banks need to meet their obligations in Central Bank money held in payment systems that are commonly operated or closely supervised by central banks (e.g. CHAPS, FedWire, Target2, which are also referred to as large value payment systems), it is of great interest to monitor these systems' participants' (mainly banks) liquidity positions.

The amount of liquidity held by banks on their accounts can be a lot less (and usually is) than the total value of transferred payments during a day. The total amount of liquidity needed by banks to settle a given set of payments is dependent on the balancedness of the circulation of money from account to account (reciprocity of payments), the timing of payments and the netting procedures used. The inability of some participants to send payments can cause severe falls in settlement ratios of payments. The failure of one participant to send payments can have negative contagion effects on other participants' liquidity positions and their potential to send payments.

By using stress tests it is possible to evaluate the short term effects of events such as bank failures or technical communication breakdowns that lead to the inability of chosen participants to send payments. These effects can be viewed as direct effects on the participant, but also as systemic contagion effects. How hard the other participants will be hit by a chosen failure scenario will be dependent on the available collateral and initial liquidity of participants, and their potential to bring in more liquidity. Stress test conducted on payment systems help to evaluate the short term adequacy and sufficiency of the prevailing liquidity levels and buffers of banks, and the contingency measures of the studied payment systems.

A financial stress test is only as good as the scenarios on which it is based. Those designing stress tests must literally imagine possible futures that the financial system might face. As an exercise of the imagination, the stress test is limited by the imaginative capacities of those designing the stress test scenarios. Sometimes, the stress test's designers fail to imagine plausible future scenarios, possibly because of professional peer pressure or groupthink within a profession or trade (witness the failure of the great majority of financial "experts" to envisage the crash of 2008) or because some things are just too horrible to imagine. The successive financial stress tests conducted by the European Banking Authority and the Committee of European Banking Supervisors in 2009, 2010 and 2011 illustrate this dynamic. The 2009 and 2010 stress tests assumed even in their adverse scenarios a relatively benign macro-economic environment of -0.6% economic growth in the Euro area; by 2011 it was clear that such assumptions were no longer just plausible, they were almost certain to happen; the adverse scenario had to be adjusted to a -4.0% growth scenario. Those reviewing and using the results of stress tests must cast a critical eye on the scenarios used in the stress test.