When selecting a security for investment, traders look at its historical volatility to help determine the relative risk of a potential trade. There are numerous metrics that measure volatility in differing contexts, and each trader has favorites. Regardless of which metric you utilize, a firm understanding of the concept of volatility and how it is measured is essential to successful investing.

Simply put, volatility is a reflection of the degree to which price moves. A stock with a price that fluctuates wildly, hits new highs and lows, or moves erratically is considered highly volatile. A stock that maintains a relatively stable price has low volatility. A highly volatile stock is inherently riskier, but that risk cuts both ways. When investing in a volatile security, the risk of success is increased just as much as the risk of failure. For this reason, many traders with a high risk tolerance look to multiple measures of volatility to help inform their trade strategies.

How to Measure Volatility

The primary measure of volatility used by traders and analysts is standard deviation. This metric reflects the average amount a stock's price has differed from the mean over a period of time. It is calculated by determining the mean price for the established period, and then subtracting this figure from each price point. The differences are then squared, summed and averaged to produce the variance.

Because the variance is the product of squares, it is no longer in the original unit of measure. Since price is measured in dollars, a metric that uses dollars squared is not very easy to interpret. Therefore, standard deviation is calculated by taking the square root of the variance, which brings it back to the same unit of measure as the underlying data set.


Calculating Volatility with Average True Range

Chartists use a technical indicator called Bollinger Bands to analyze standard deviation over time. Bollinger Bands are comprised of three lines: the simple moving average (SMA) and two bands placed one standard deviation above and below the SMA. The SMA is a moving average that changes with each session to incorporate that day's changes, and the outer bands mirror that change to reflect the corresponding adjustment to the standard deviation. Standard deviation is reflected by the width of the Bollinger Bands. The wider the Bollinger Bands, the more volatile a stock's price within the given period. A stock with low volatility has very narrow Bollinger Bands that sit close to the SMA.

In the example below, a chart of Snap Inc. (SNAP) with Bollinger Bands enabled is shown. For the most part, the stock traded within the tops and bottoms of the bands over a six month range between about $12-18 per share.

For a more comprehensive assessment of risk, measure multiple forms of volatility.

Where standard deviation measures a security's price movements compared to its average over time, beta measures a security's volatility relative to that of the wider market. A beta of 1 means the security has volatility that mirrors the degree and direction of the market as a whole. This means that if the S&P 500 takes a sharp dip, the stock in question is likely to follow suit.

Relatively stable securities, such as utilities, have beta values of less than 1, reflecting their lower volatility. Stocks in rapidly changing fields, especially in the technology sector, have beta values of more than 1. A beta of 0 indicates the underlying security has no volatility. Cash is an excellent example, if no inflation is assumed.