What if there were a technique that allowed investors to determine whether a negative event has impacted their portfolio’s value, or what might happen to their holdings if the worst comes true? As it turns out, there is. It is called “scenario analysis.” Here it is explained.
With this process, investors can estimate a portfolio’s expected value after a given period during which changes in portfolio securities are assumed, or after occurrences such as an interest rate change.
In other words, the strategy is often employed to estimate alterations to a portfolio’s value following an unfavorable occurrence and may be used to assess a theoretical worst-case situation.
In addition to an investment strategy, scenario analysis is also used with corporate finance.
With this technique, varying reinvestment rates are computed for anticipated returns that are then reinvested.
Scenario analysis is based on statistical and mathematical principles and provides a way to estimate portfolio value changes due to possible occurrences, or “scenarios.”
Such analyses also follow the principles of sensitivity analysis, which is how a dependent variable is affected by the different values of an independent variable.
Scenario analysis can be employed to determine the level of investment risk for a range of potential events. An investor can use analysis results to determine whether the risk level is acceptable.
A common approach in scenario analysis calls for determining daily or monthly security returns’ standard deviation. That is followed by computing the portfolio’s expected value if each security yields returns that are two to three standard deviations over and under the average return. In simulating such extremes, an analyst can be reasonably certain of a portfolio’s value change during a given period.
Scenarios under consideration can be related to a sole variable – a new product launch, for example – or multiple factors, such as product launch results combined with prospective changes in a competitor’s business activities. The aim is to assess extreme outcome results to establish the investment strategy.
Companies can also employ scenario analysis to help them make decisions regarding, for example, the facility they should buy for operations. Considerations could include differences in rent, insurance, utility fees, or any advantage that favors one location over the other.
Managers can use scenario analysis for almost any decision, especially those having to do with competitive strategy. In other words, the strategy permits managers to test strategic proposals and assess how they would turn out under varying conditions.
Companies can use the tool to study the varying prospective impact of unfavorable and favorable events, including:
Note that consumers can also use scenario analysis to assess the varying outcomes of using credit for a purchase, rather than saving the funds to purchase the item with cash. They can also use it to consider possible financial changes that might occur when mulling a job offer.
Stress testing, a scenario analysis type that specifically considers worst-case scenarios, is commonly employed using a computerized simulation technique to gauge the resilience of investment holdings and institutions against possible future scenarios.
The financial industry frequently uses such testing to help assess investment risk and asset adequacy, and to gauge internal processes and controls. Regulators in recent years have required stress tests to make certain that capital holdings and other assets are sufficient.
There are at least three scenario types:
Say there is a company called ABC Inc. that produces carpenter tools. It has an idea for a new tool that can not only help sharpen iron but can clean itself afterward. The rub is that it will take around a year to bring the tool to market, and financial analysts are expecting economic headwinds during that period.
Such conditions can impact varying factors, from consumer demand to the prices of raw materials. The company could consider several scenarios, each one producing different assumptions.
In the best-case scenario, ABC Inc. could experience rising revenues because more people are at home and using DIY methods. In the worst case, demand drops while costs rise across the board. With a base case, existing trends continue.
While sensitivity analysis is a type of scenario analysis, there are differences between the two. The former gauges the effect of changing only one variable at a time. While scenario analysis considers a broad range of potential outcomes, it assesses the impact of manipulating all variables simultaneously
The primary benefit of scenario analysis is that it results in an extensive assessment of all potential outcomes, which permits analysts to test decisions, identify prospective risks, and grasp the potential effect of certain variables.
It’s also an educational tool for business partners, improves scenario analysis efficiency, and helps with the cross-checking of model integrity.
In terms of challenges, the chief issue is that false assumptions can result in models that are far off the mark. There is also the potential for user bias and for scenario analysis to be significantly dependent on historical data.
Among investors, scenario analysis is more applicable to those with positions in the stock market, since investors can use it to find a portfolio’s likely value following assumed changes or occurrences such as a change in interest rate.
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Alternative investments can be a good way to help accomplish this. Traditional portfolio asset allocation envisages a 60% public stock and 40% fixed income allocation. However, a more balanced 60/20/20 or 50/30/20 split, incorporating alternative assets, may make a portfolio less sensitive to public market short-term swings.
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In some cases, this risk can be greater than that of traditional investments.
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As a tool, scenario analysis can be very useful for investors and managers in terms of navigating future uncertainty. It provides a way to analyze the future in a structured and rational manner. However, it is only as effective as user inputs and assumptions.
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