Standard Deviation and Risk

Risk measurement is a very big component of many sectors of the finance industry. While it plays a role in economics and accounting, the impact of accurate or faulty risk measurement is most clearly illustrated in the investment sector.

Knowing the probability that a security—whether you invest in stocks, options, or mutual funds—moves in an unexpected way can be the difference between a well-placed trade and bankruptcy. Traders and analysts use a number of metrics to assess the volatility and relative risk of potential investments, but the most common metric is standard deviation.

Read on to find out more about standard deviation, and how it helps determine risk in the investment industry.

What Is Standard Deviation?

Standard deviation is a basic mathematical concept that measures volatility in the market or the average amount by which individual data points differ from the mean. Simply put, standard deviation helps determine the spread of asset prices from their average price.

When prices swing up or down significantly, the standard deviation is high, meaning there is high volatility. On the other hand, when there is a narrow spread between trading ranges, the standard deviation is low, meaning volatility is low. What can we determine by this? Volatile prices mean standard deviation is high, and it is low when prices are relatively calm and not subject to wild swings.

While standard deviation is an important measure of investment risk, it is not the only one. There are many other measures investors can use to determine whether an asset is too risky for them—or not risky enough.

Calculating Standard Deviation

Standard deviation is calculated by first subtracting the mean from each value, and then squaring, adding, and averaging the differences to produce the variance.

While variance itself is a useful indicator of range and volatility, the squaring of the individual differences means they are no longer reported in the same unit of measurement as the original data set.

For stock prices, the original data is in dollars and variance is in dollars squared, which is not a useful unit of measure. Standard deviation is simply the square root of the variance, bringing it back to the original unit of measure and making it much simpler to use and interpret.

Relating Standard Deviation to Risk

In investing, standard deviation is used as an indicator of market volatility and thus of risk. The more unpredictable the price action and the wider the range, the greater the risk. Range-bound securities, or those that do not stray far from their means, are not considered a great risk. That’s because it can be assumed—with relative certainty—that they continue to behave in the same way. A security with a very large trading range and a tendency to spike, reverse suddenly, or gap is much riskier, which can mean a larger loss. But remember, risk is not necessarily a bad thing in the investment world. The riskier the security, the greater potential it has for payout.

When using standard deviation to measure risk in the stock market, the underlying assumption is that the majority of price activity follows the pattern of a normal distribution. In a normal distribution, individual values fall within one standard deviation of the mean, above or below, 68% of the time. Values are within two standard deviations 95% of the time.

For example, in a stock with a mean price of $45 and a standard deviation of $5, it can be assumed with 95% certainty the next closing price remains between $35 and $55. However, price plummets or spikes outside of this range 5% of the time. A stock with high volatility generally has a high standard deviation, while the deviation of a stable blue-chip stock is usually fairly low.

So what can we determine from this? The smaller the standard deviation, the less risky an investment will be, dollar-for-dollar. On the other hand, the larger the variance and standard deviation, the more volatile a security. While investors can assume price remains within two standard deviations of the mean 95% of the time, this can still be a very large range. As with anything else, the greater the number of possible outcomes, the greater the risk of choosing the wrong one.