Earlier this year the Basel Committee on Banking Supervision issued the paper Principles for sound stress testing practices and supervision. For full text of May 2009 final paper, Click Here.
“Stress Testing” has obviously gotten a lot of press this year; but what does it really mean?
What is commonly known as “Stress testing” could also be defined in terms of:
- Sensitivity analysis: the identification of how risky portfolios respond to shifts in relevant economic variables or underlying risk parameters or;
- Scenario Analysis: an assessment of the resilience of a portfolio, financial institution or the financial system as a whole in this age of systemic-risk-awareness to severe but plausible scenarios.
Sensitivity analysis has historically been the methodology used to quantify portfolio risk. It is however, a limited approach that might best be described as one-dimensional.
Scenario analysis is a dynamic and systematic process for analyzing possible future events by considering various alternative outcomes. It is designed to allow improved decision-making, invoking consideration of negative outcomes and implications on business strategy, franchise, risks, and rewards.
Scenario Analysis is geared towards enabling decision making on risk appetite versus risk levels, asset allocation, client and product segmentation strategies, implicit and explicit diversification tactics, and insurance/hedge considerations; institutions can also compute scenario-weighted expected returns, and improve their knowledge of the unknown i.e. potential unexpected losses and economic/regulatory capital adequacy. Scenario analysis can also be used to illuminate wild cards and “black swans”.
Scenario based stress testing defines a scenario and uses specific algorithms (ideally full revaluations) to determine the expected impact on a portfolio’s return should such a scenario occur.
There are typically three types of scenarios:
- Extreme Event: Hypothesize the portfolio (or enterprise) returns given the recurrence of a historical event. Current positions/risk exposures are combined with 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 a 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), or custom series (e.g., exchange rates). Using regression analysis, new factor returns are estimated as a result of the shock.
A mathematical approach to scenario analysis looks to estimate expected cash flows under various situations. The expected cash flows used to value risky assets can represent a probability-weighted average of cash flows under all possible scenarios, or, they can simply be the cash flows under a single most likely scenario. In either case the scenario based cash flows will be different from expectations:
For example, instead of doing financial projections on a "best estimate" basis, a company may do Stress Testing, against, say, the following distinct scenarios
- What happens if the equity market crashes by more than x% this year?
- What if interest rates go up at least y%?
- What if oil prices rise by 300%?
- What if half the instruments in the portfolio terminate their contacts in the 5th year?
One good definition of ‘risk’ is the extent to which actual outcomes may be different from what is expected. The creation of a robust stress testing program that includes scenario analysis will go a long way towards minimizing future surprises.
Please keep the comments coming. I will look to summarize the discussion in my next post a week or so from now. I also want to address the use of stress-testing in the real world (not just running some numbers in a vacuum that nobody can relate to!)
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7 comments:
The Stress Testing and Scenario analysis serves a very limited purpose because risk is dynamic. It mutates to different forms taking the environment in which it grows. It is, therefore, more appropriate to think differently. Everytime we face a crisis we design some tests and prescribe some rules and regulations. The industry jumps into bandwagon with all sincerity to follow it. we end up at same point again. It happens becuase we are not thinking differently taking into account our own environment and entropy. Although, the best practices acts as some milestones that are required to achieve at the floor level, we nood to think differently to reach the ceiling.
It is not clear if regulations requiring use of a robust stress test model, built on the framework of scenario analysis, would have prevented the recent financial crisis. It does seem very plausible that it would have at least forced real estate market participants (i.e., lenders, structured product dealers, risk managers, lawyers, investors AND government policymakers to name a few) to consider alternatives to the “hockey-stick” assumption made when placing bets on a market. Future implementation of this dynamic tool along with thoughtful application should help prevent a repeat of the past.
Jaidev
You make good points here but the key to this - beyond the maths, beyond the OR / statistics / econometrics - is that the senior management GET IT.
The stress tests do serve the objective of reducing the risk of nasty surprises. I would also like to add that the stress tests, particularly, the scenario based stress tests should be presented before the business owners who are impacted by the respective asset classes, much like business proposals are presented before Committees with representation of Risk Management functions. A good business strategy should have embedded in it the stress tests so that there is a hedge built in terms of product, sectoral, geographic and customer diversifications. Then the stress tests would have realised their purpose, more fully.
Stress tests can provide indications of the level of resources that would need to be available to tide over extreme situations and extreme tail events. Too much would obviously have return implications. Scenarios constructed must be 'plausible', but, nasty surprises will continue to happen and historical scenarios may not be exactly repeated. Central Banks use this to push banks to raise additional capital (over minimum regulatory capital) and they are already active through Pillar II guidelines within Basel II.
I think rather than placing so much emphasis on the "quantitative" result of stress testing a better benefit should be that if done properly and consistently it will force the user to think and have a broader view of factors in its internal and external environment that can affect its business and their likely effects if they move adversely.
Stress testing using sensitivity and scenario analysis can be effective tools to understand potential risks. However, the effectiveness relies on the key decision makers (investment managers, risk managers, and senior managers) ability to align their interests and come up with contingency plans and actions. Too often short term profitability takes precidence over hedging or concerns over small probability events. No model or quantitative tool will be exact and without problems regarding its assumptions, but it is not useless and is helpful in understanding risk appetite. It is only useless if the intentions of the decision makers are not sincere (wanting to reduce risk) but rather only seek compliance and or not able to truely voice their opinion regarding risk due to fear of losing their job.
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