ETF Series Standard Deviation
| TRFM ETF | | | USD 56.41 -1.02 -1.78% |
The Standard Deviation is a measure of how spread out the prices or returns of an asset are on average. It is the most widely used risk indicator in the field of investing and finance. Standard Deviation is commonly used to measure confidence in statistical conclusions regarding certain equity instruments or portfolios of equities. Below is ETF Series's current Standard Deviation with peer comparisons and related risk metrics.
Current Standard Deviation Value
ETF Series carries a Standard Deviation of 1.72, consistent with moderate price variability. This places ETF Series within the typical volatility range for ETF.
Standard Deviation | = | SQRT(V) |
| = | 1.72 | |
Standard Deviation Peers Comparison
Among sector peers, ETF Series's Standard Deviation of 1.72 is above the 1.29 group average. The range runs from 0.435 (FT Cboe Vest) to 3.36 (Spear Alpha ETF). ETF Series has exhibited greater price dispersion than the peer average over the measured period.
Standard Deviation Relative To Other Indicators
The chart below plots Standard Deviation against Maximum Drawdown for ETF Series and its peers. Each point represents one equity — position along the horizontal axis shows Standard Deviation while the vertical axis shows Maximum Drawdown. Equities that cluster in different quadrants carry distinct risk-return profiles. Use the dropdowns to swap in other indicators for either axis.
ETF Series shows nearly
4.26 of Maximum Drawdown per unit of Standard Deviation (
1.72 versus
7.34 ). This indicates Maximum Drawdown is significantly higher than Standard Deviation for ETF Series.
Methodology, Assumptions & Data Sources
ETF Series' Standard Deviation currently stands at 1.72. Standard Deviation for ETF Series is derived by applying a defined formula to historical price observations, producing a time-series of comparable readings. Price data is sourced from standardized end-of-day feeds across supported exchanges, normalized for corporate actions. Indicator accuracy depends on data continuity across the calculation period. Gaps in trading history may affect the output.
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