Semivariance

Semivariance

Semivariance is a measurement of data that can be used to estimate the potential downside risk of an investment portfolio. Spreadsheet programs can be useful in calculating semivariance for your portfolio. Semivariance \= 1 n × ∑ r t < Average n ( Average − r t ) 2 where: n \= The total number of observations below the mean r t \= The observed value \\begin{aligned} &\\text{Semivariance}=\\frac1n\\times\\sum^n\_{r\_t<\\text{Average}}(\\text{Average}-r\_t)^2\\\\ &\\textbf{where:}\\\\ &n = \\text{The total number of observations below the mean}\\\\ &r\_t = \\text{The observed value}\\\\ &\\text{Average} = \\text{The mean or target value of the dataset} \\end{aligned} Semivariance\=n1×rt<Average∑n(Average−rt)2where:n\=The total number of observations below the meanrt\=The observed value Semivariance is similar to variance, but it only considers observations that are below the mean. To use a spreadsheet program to calculate semivariance: Create a column — for example, column A — that consists of all returns in the portfolio. Remove all returns above the mean from column A. In column B, subtract the returns remaining in column A from the mean. In column C, square the difference, find the sum, and divide the sum by the number of returns that fall below the mean. Different spreadsheets may have different functionality and some have easier ways or shortcuts to do this calculation. Semivariance is calculated by measuring the dispersion of all observations that fall below the mean or target value of a set of data. Semivariance can be used to calculate the average loss that a portfolio could incur because it neutralizes all values above the mean, or above an investor's target return.

The semivariance formula can be used to measure a portfolio's downside risk.

What Is a Semivariance?

Semivariance is a measurement of data that can be used to estimate the potential downside risk of an investment portfolio. Semivariance is calculated by measuring the dispersion of all observations that fall below the mean or target value of a set of data. Semivariance is an average of the squared deviations of values that are less than the mean.

The semivariance formula can be used to measure a portfolio's downside risk.
Semivariance only considers observations that are below the mean of a data set.
Spreadsheet programs can be useful in calculating semivariance for your portfolio.

Understanding Semivariance

The Formula for Semivariance Is

Semivariance = 1 n × ∑ r t < Average n ( Average − r t ) 2 where: n = The total number of observations below the mean r t = The observed value \begin{aligned} &\text{Semivariance}=\frac1n\times\sum^n_{r_t<\text{Average}}(\text{Average}-r_t)^2\\ &\textbf{where:}\\ &n = \text{The total number of observations below the mean}\\ &r_t = \text{The observed value}\\ &\text{Average} = \text{The mean or target value of the dataset} \end{aligned} Semivariance=n1×rt<Average∑n(Average−rt)2where:n=The total number of observations below the meanrt=The observed value

What Does Semivariance Tell You?

Semivariance is similar to variance, but it only considers observations that are below the mean. Semivariance is a useful tool in portfolio or asset analysis because it provides a measure for downside risk.

While standard deviation and variance provide measures of volatility, semivariance only looks at the negative fluctuations of an asset. Semivariance can be used to calculate the average loss that a portfolio could incur because it neutralizes all values above the mean, or above an investor's target return.

For risk-averse investors, determining optimal portfolio allocations by minimizing semivariance could reduce the likelihood of a large decline in the portfolio's value.

Calculate With a Spreadsheet

To use a spreadsheet program to calculate semivariance:

Different spreadsheets may have different functionality and some have easier ways or shortcuts to do this calculation.

Related terms:

Dispersion

Dispersion is a statistical measure of the expected volatility of a security based on historical returns. read more

Downside Risk

Downside risk is an estimation of a security's potential loss in value if market conditions precipitate a decline in that security's price. read more

Quartile

A quartile is a statistical term describing a division of a data set into four defined intervals. read more

Residual Sum of Squares (RSS)

The residual sum of squares (RSS) is a statistical technique used to measure the variance in a data set that is not explained by the regression model. read more

Risk Averse

The term risk-averse describes the investor who prioritizes the preservation of capital over the potential for a high return. read more

Semi-Deviation

Semi-deviation is a method of evaluating the below-mean fluctuations in the returns on investment. It is used as an alternative to standard deviation. read more

Standard Deviation

The standard deviation is a statistic that measures the dispersion of a dataset relative to its mean. It is calculated as the square root of variance by determining the variation between each data point relative to the mean. read more

T-Test

A t-test is a type of inferential statistic used to determine if there is a significant difference between the means of two groups, which may be related in certain features. read more

Variance , Formula, & Calculation

Variance is a measurement of the spread between numbers in a data set. Investors use the variance equation to evaluate a portfolio’s asset allocation. read more

Volatility : Calculation & Market Examples

Volatility measures how much the price of a security, derivative, or index fluctuates. read more