November 1, 2018
CFA Event | Stress Testing for Investment Decision Support; the Best and Next Practices
Stress tests are designed to estimate the impact of adverse market movements on a portfolio. These market scenarios can be extreme but should always be plausible. For example, changes in monetary policy, increasing inflation, or political instability can be modeled as low-probability events. Meaningful stress tests provide a forward-looking assessment of risk, overcome limitations of simulation models, and help aid the development of risk mitigation techniques.
Under a risk management framework, stress tests are an indispensable complement to statistical models such as value at risk (VaR). While the risk factors, distributional assumptions, and pricing functions of VaR models vary, even the most sophisticated approaches are deficient in abnormal or crisis periods. One might be tempted to look further in the tail of the loss distribution for extreme events (with greater percentiles or a metric such as CVaR). But if the loss distribution is derived under normal market conditions, it might not apply in a crisis period. In fact, VaR models do not adequately capture volatility jumps or changing correlation structures and perform poorly when liquidity dries up, as seen by the Lehman crisis.
Stress tests overcome the shortcomings of statistical models. Stress tests need not reflect correlations under normal periods and are designed by specifying directional shocks to parsimonious or granular risk factors. Since stress test results are represented as P&Ls, they are more transparent and intuitive than VaR or CVaR. In addition, they help design better hedges so that managers can mitigate unacceptable levels of risk. In this presentation we will focus on the design of relevant scenarios for quantifying the potential impact of various geopolitical and macro-economic risks to a model portfolio.