30-Day Annualized Volatility

The calculation takes the standard deviation of daily logarithmic returns over the trailing thirty days and multiplies it by the square root of 365, because digital assets trade every calendar day. The result is expressed as an annualized percentage so that it can be compared with volatility figures from other markets. It is a description of realized past movement, not a forecast.

इसकी गणना कैसे होती है

standard deviation of daily log returns over the trailing 30 days x sqrt(365) x 100

यह कहाँ भ्रमित करता है

Annualizing a thirty-day sample assumes returns are independent and identically distributed, and digital-asset returns are neither: volatility clusters, so a calm month produces a figure that collapses in a single stressed week. The annualization convention itself differs between providers, with some using the square root of 365 for continuous trading and others carrying over the equity convention of 252, which changes the published number by roughly twenty percent for no economic reason. With only thirty observations, one or two extreme days dominate the estimate, and standard deviation weights upside and downside moves identically. For stablecoins the reading sits near zero right up until a peg break, so it carries essentially no information about their actual failure mode.

equity की तुलना, और यह क्यों विफल होती है

Realized volatility on an equity; the estimator is the same, but equity return distributions have thinner tails and equity markets close each night, so the annualization assumption is far less strained there.

उच्च या निम्न मान पढ़ना

A higher figure means daily price changes over the past month were larger in dispersion than for an asset with a lower figure. Volatility measures the size of moves, not their direction, and a low recent reading does not persist by itself.