“Stress testing” has been adopted as a generic term describing various techniques used by banks to gauge their potential vulnerability to exceptional, but plausible, events. Stress testing addresses the large moves in key market variables of that kind that lie beyond day to day risk monitoring but that could potentially occur. The process of stress testing, therefore, involves first identifying these potential movements, including which market variables to stress, how much to stress them by, and what time frame to run the stress analysis over.
Once these market movements and underlying assumptions are decided upon, shocks are applied to the portfolio. Revaluing the portfolios allows one to see what the effect of a particular market movement has on the value of the portfolio and the overall Profit and Loss. Stress test reports can be constructed that summarise the effects of different shocks of different magnitudes. Normally, then there is some kind of reporting procedure and follow up with traders and management to determine whether any action need to be taken in response. Stress testing and value-at-risk*i Stress tests supplement value-at-risk (VaR). VaR is thought to be a critical tool for tracking the riskiness of a firm’s portfolio on a day-to-day level, and for assessing the risk-adjusted performance of individual business units.
However, VaR has been found to be of limited use in measuring firms’ exposures to extreme market events. This is because, by definition, such events occur too rarely to be captured by empirically driven statistical models. Furthermore, observed correlation patterns between various financial prices (and thus the correlations that would be estimated using data from ordinary times) tend to change when the price movements themselves are large. Stress tests offer a way of measuring and monitoring the portfolio consequences of extreme price movements of this type. Stress Testing Techniques: Stress testing covers many different techniques.
The four discussed here are listed in the Table below along with the information typically referred to as the “result” of that type of a stress test. Stress Testing Techniques? Technique What is the “stress test result” Simple Sensitivity Test Change in portfolio value for one or more shocks to a single risk factor Scenario Analysis (hypothetical or historical) Change in portfolio value if the scenario were to occur Maximum loss Sum of individual trading units’ worst-case scenarios Extreme value theory Probability distribution of extreme losses A simple sensitivity test isolates the short-term impact on a portfolio’s value of a series of predefined moves in a particular market risk factor. For example, if the risk factor were an exchange rate, the shocks might be exchange rate changes of +/_ 2 percent, 4 percent, 6 percent and 10 percent. A scenario analysis specifies the shocks that might plausibly affect a number of market risk factors simultaneously if an extreme, but possible, event occurs.
It seeks to assess the potential consequences for a firm of an extreme, but possible, state of the world. A scenario analysis can be based on an historical event or a hypothetical event. Historical scenarios employ shocks that occurred in specific historical episodes. Hypothetical scenarios use a structure of shocks thought to be plausible in some foreseeable, but unlikely circumstances for which there is no exact parallel in recent history. Scenario analysis is currently the leading stress testing technique. A maximum loss approach assesses the riskiness of a business unit’s portfolio by identifying the most potentially damaging combination of moves of market risk factors.
Interviewed risk managers who use such “maximum loss” approaches find the output of such exercises to be instructive but they tend not to rely on the results of such exercises in the setting of exposure limits in any systematic manner, an implicit recognition of the arbitrary character of the combination of shocks captured by such a measure. Extreme value theory (EVT) is a means to better capture the risk of loss in extreme, but possible, circumstances. EVT is the statistical theory on the behaviour of the “tails” (i.e., the very high and low potential values) of probability distributions. Because it focuses only on the tail of a probability distribution, the method can be more flexible. For example, it can accommodate skewed and fat-tailed distributions.
A problem with the extreme value approach is adapting it to a situation where many risk factors drive the underlying return distribution. Moreover, the usually unstated assumption that extreme events are not correlated through time is questionable. Despite these drawbacks, EVT is notable for being the only stress test technique that attempts to attach a probability to stress test results. What Makes a good Stress Test A good stress test should ? be relevant to the current position ? consider changes in all relevant market rates ? examine potential regime shifts (whether the current risk parameters will hold or break down) ? spur discussion ? consider market illiquidity, and ? consider the interplay of market and credit risk How should risk managers use stress tests: Stress tests produce information summarising the firm’s exposure to extreme, but possible, circumstances.
The role of risk managers in the bank should be assembling and summarising information to enable senior management to understand the strategic relationship between the firm’s risk-taking (such as the extent and character of financial leverage employed) and risk appetite. Typically, the results of a small number of stress scenarios should be computed on a regular basis and monitored over time. Some of the specific ways stress tests are used to influence decision-making are to: ? manage funding risk ? provide a check on modelling assumptions ? set limits for traders ? determine capital charges on trading desks’ positions Manage funding risk: Senior managers use stress tests to help them make decisions regarding funding risk. Managers have come to accept the need to manage risk exposures in anticipation of unfavourable circumstances.
The significance of such information will vary according to a bank’s exposure to funding or liquidity risk. Provide a check on modelling assumptions: Scenario analysis is also used to highlight the role of particular correlation and volatility assumptions in the construction of banks’ portfolios of market risk exposures. In this case, scenario analysis can be thought of as a means through which banks check on the portfolio’s sensitivity to assumptions about the extent of effective portfolio diversification. Set limits for traders: Stress tests are also used to set limits. Simple sensitivity tests may be used to put hard limits on bank’s market risk exposures. Determine capital charges on trading desks’ positions: Banks may also initiate capital charges based on hypothetical losses under certain stress scenarios.
The capital charges are deducted from each business unit’s bonus pool. This procedure may be designed to provide each business unit with an economic incentive to reduce the risk of extreme losses. Limitations of Stress Tests Stress testing can appear to be a straightforward technique. In practice, however, stress tests are often neither transparent nor straightforward. They are based on a large number of practitioner choices as to what risk factors to stress, how to combine factors stressed, what range of values to consider, and what time frame to analyse. Even after such choices are made, a risk manager is faced with the considerable tasks of sifting through results and identifying what implications, if any, the stress test results might have for how the firm should manage its risk-taking activities.
A well-understood limitation of stress testing is that there are no probabilities attached to the outcomes. Stress tests help answer the question “How much could be lost?” The lack of probability measures exacerbates the issue of transparency and the seeming arbitrariness of stress test design. Systems incompatibilities across business units make frequent stress testing costly for some firms, reflecting the limited role that stress testing had played in influencing the firm’s prior investments in information technology.
