Elm Market Maximum Drawdown
Maximum Drawdown (or MDD) is another indicator of risk. It is the reduction in asset value after a series of losing trades. This is normally calculated by getting the difference between a relative peaks in equity capital minus a relative trough. Below is Elm Market's current Maximum Drawdown with peer comparisons and related risk metrics.
Current Maximum Drawdown Value
Elm Market registers a Maximum Drawdown of 3.6, reflecting a contained peak-to-trough loss. Elm Market's maximum drawdown has remained under 10%, indicating limited downside exposure.
Maximum Drawdown | = | MAX(HIGH - LOW) |
| = | 3.6 | |
| MAX | = | Maximum notation for the range of returns on Elm Market |
Maximum Drawdown Peers Comparison
The peer group averages 4.96 for Maximum Drawdown, with Elm Market at 3.6 falling below that level. Readings span 2.8 (Invesco SAMPP 500) to 8.01 (Invesco DWA Developed). Elm Market's shallower drawdown relative to peers indicates more contained historical downside.
Maximum Drawdown Relative To Other Indicators
The chart below plots Maximum Drawdown against Maximum Drawdown for Elm Market and its peers. Each point represents one equity — position along the horizontal axis shows Maximum Drawdown 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.
Elm Market shows nearly
1.00 of Maximum Drawdown per unit of Maximum Drawdown (
3.60 versus
3.60 ). The two measures are closely aligned in magnitude for Elm Market.
Compare Elm Market to PeersMethodology, Assumptions & Data Sources
Elm Market's Maximum Drawdown currently stands at 3.6. Elm Market's Maximum Drawdown is computed from historical closing prices over the selected time horizon, applying the indicator's defined mathematical transformation to raw price data. Inputs are drawn from end-of-day closing prices reported by supported exchanges, adjusted for splits and dividends where applicable. Indicator accuracy depends on data continuity across the calculation period. Gaps in trading history may affect the output.
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