Standalone Risk: Overview, Examples, and Formulas

What Is Standalone Risk?

Standalone risk is the risk associated with a single operating unit of a company, a company division, or asset, as opposed to a larger, well-diversified portfolio.

Understanding Standalone Risk

All financial assets can be examined in the context of a broader portfolio or on a stand-alone basis, when the asset in question is thought to be isolated. While a portfolio context takes all of the investments and assessments into account when calculating risk, standalone risk is calculated assuming that the asset in question is the only investment that the investor has to lose or gain.

Standalone risk represents the risks created by a specific asset, division, or project. It risk measures the dangers associated with a single facet of a company's operations, or the risks from holding a specific asset, such as a closely held corporation.

For a company, computing standalone risk can help determine a project's risk as if it were operating as an independent entity. The risk would not exist if those operations ceased to exist. In portfolio management, standalone risk measures the risk of an individual asset that cannot be reduced through diversification.

Investors may examine the risk of a standalone asset to predict the expected return of an investment. Standalone risks have to be carefully considered because as a limited asset, an investor either stands to see a high return if its value increases or a devastating loss if things don't go according to plan.

Measuring Standalone Risk

Standalone risk can be measured with a total beta calculation or through the coefficient of variation (CV).

Total Beta

Beta reflects how much volatility a specific asset will experience relative to the overall market. Meanwhile, total beta, which is accomplished by removing the correlation coefficient from beta, measures the standalone risk of the specific asset without it being part of a well-diversified portfolio.

The Coefficient of Variation (CV)

The CV is a measure used in probability theory and statistics that creates a normalized measure of dispersion of a probability distribution. After calculating the CV, its value can be used to analyze an expected return along with an expected risk value on a standalone basis.

A low CV would indicate a higher expected return with lower risk, while a higher value CV would signify a higher risk and lower expected return. The CV is thought to be especially helpful because it is a dimensionless number, meaning that, in terms of financial analysis, it does not require the inclusion of other risk factors, such as market volatility.