Match Downside Deviation

MTCH Stock  USD 36.75  1.09  3.06%   
Downside Deviation (or DD) is measured by target semi-deviation (the square root of target semi-variance) and is termed downside risk. It is expressed in percentages and therefore allows for rankings in the same way as standard deviation. An intuitive way to view the downside risk is the annualized standard deviation of returns below the target. Below is Match's current Downside Deviation with peer comparisons and related risk metrics.

Current Downside Deviation Value

A Downside Deviation of 2.54 for Match signals moderate price variability. This places Match within the typical volatility range for Interactive Media & Services.

Downside Deviation

=

SQRT(DV)

 = 
2.54
SQRT = Square root notation
DV =   Downside Variance of returns over selected period

Downside Deviation Peers Comparison

Downside Deviation Relative To Other Indicators

The chart below plots Downside Deviation against Maximum Drawdown for Match and its peers. Each point represents one equity — position along the horizontal axis shows Downside 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.
At 2.54 for Downside Deviation and 11.56 for Maximum Drawdown, Match's cross-indicator ratio sits almost 4.55 . This indicates Maximum Drawdown is significantly higher than Downside Deviation for Match.
Compare Match to Peers

Methodology, Assumptions & Data Sources

Match's Downside Deviation currently stands at 2.54. The Downside Deviation for Match applies a standardized calculation to daily closing prices and, where applicable, volume data across the selected period. Price data is sourced from standardized end-of-day feeds across supported exchanges, normalized for corporate actions. Match operates in the communication services sector, which may exhibit distinct volatility and momentum characteristics relative to the broader market. Indicator accuracy depends on data continuity across the calculation period. Gaps in trading history may affect the output.

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