Standard deviation measures how spread out numbers are around their average — small means they huddle close, large means they scatter. It is the raw ingredient behind almost every risk metric on the site.
Take the average of your numbers. Subtract the average from each value to get its distance from the middle, square those distances (so positives and negatives don't cancel), average the squares, then take the square root to return to the original units. Example (illustrative): daily returns of +1%, −1%, +3%, −1%, +2% average +0.8%; the squared distances average about 2.56, so the standard deviation is roughly 1.6% per day — how far a typical day strays from the average day.
Standard deviation counts upside and downside swings equally, but most investors only lose sleep over the downside — which is why downside-focused cousins like the Sortino ratio and Value at Risk exist.
Variance is the average squared distance from the mean; standard deviation is its square root, which brings the number back into the same units as the data so it is easier to interpret.
In finance, volatility usually IS the standard deviation of a stock's returns, most often annualised — so they measure the same thing.
It counts upside and downside swings equally and assumes the future spread resembles the past. Downside measures like Sortino and Value at Risk address the first gap.
Browse all S&P 500 tickers to see this metric applied to individual companies.
Educational research only — not investment advice.