BlackRock Industry Expected Short fall
| INRO ETF | | | 35.16 0.63 1.82% |
Expected shortfall (or ES) is a risk measure that evaluates the market risk of an equity instrument. It is an alternative to value at risk that is more sensitive to the shape of the loss distribution in the tail of the distribution. The expected shortfall at a particular level is the expected return on the portfolio in the worst percent of the cases. Expected shortfall is also called conditional value at risk (CVaR), average value at risk (AVaR), and expected tail loss (ETL). Below is BlackRock Industry's current Expected Short fall with peer comparisons and related risk metrics.
Current Expected Short fall Value
BlackRock Industry carries a Expected Short fall of
-0.91, consistent with its current reading on this measure. This reflects BlackRock Industry's positioning relative to its own recent range within ETF.
Expected Shortfall | = | Conditional VAR |
| = | -0.91 | |
Expected Short fall Peers Comparison
The peer group averages -0.94 for Expected Short fall, with BlackRock Industry at -0.9107 falling above that level. Readings span -1.3306 (Clough Select Equity) to 0.0 ().
Expected Short fall Relative To Other Indicators
The chart below plots Expected Short fall against Maximum Drawdown for BlackRock Industry and its peers. Each point represents one equity — position along the horizontal axis shows Expected Short fall 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.
Compare BlackRock Industry to PeersMethodology, Assumptions & Data Sources
BlackRock Industry's Expected Short fall currently stands at -0.91. The Expected Short fall for BlackRock Industry is produced by transforming raw price history into a standardized measure according to the indicator's defined methodology. Data sources include daily closing prices from supported exchanges, with standard corporate action adjustments applied. Indicator accuracy depends on data continuity across the calculation period. Gaps in trading history may affect the output.
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