Scenario Analysis - Financial Applications

Financial Applications

For example, in economics and finance, a financial institution might attempt to forecast several possible scenarios for the economy (e.g. rapid growth, moderate growth, slow growth) and it might also attempt to forecast financial market returns (for bonds, stocks and cash) in each of those scenarios. It might consider sub-sets of each of the possibilities. It might further seek to determine correlations and assign probabilities to the scenarios (and sub-sets if any). Then it will be in a position to consider how to distribute assets between asset types (i.e. asset allocation); the institution can also calculate the scenario-weighted expected return (which figure will indicate the overall attractiveness of the financial environment). It may also perform stress testing, using adverse scenarios.

Depending on the complexity of the problem scenario analysis can be a demanding exercise. It can be difficult to foresee what the future holds (e.g. the actual future outcome may be entirely unexpected), i.e. to foresee what the scenarios are, and to assign probabilities to them; and this is true of the general forecasts never mind the implied financial market returns. The outcomes can be modeled mathematically/statistically e.g. taking account of possible variability within single scenarios as well as possible relationships between scenarios. In general, one should take care when assigning probabilities to different scenarios as this could invite a tendency to consider only the scenario with the highest probability.

Financial institutions can take the analysis further by relating the asset allocation that the above calculations suggest to the industry or peer group distribution of assets. In so doing the financial institution seeks to control its own business risk rather than the client's risk portfolio.