Sigma Lithium Skewness

SGML Stock  USD 22.84  -0.01  -0.04%   
Skewness describes asymmetry of returns from the normal distribution. It can come in the form of negative skewness or positive skewness, depending on whether data points are skewed to the left (negative skew) or to the right (positive skew) of the data average. Below is Sigma Lithium's current Skewness with peer comparisons and related risk metrics.

Current Skewness Value

Sigma Lithium registers a Skewness of 1.28, reflecting strong positive skew — the return distribution has a substantially heavier right tail. Sigma Lithium's returns show large upside outliers that exceed any downside moves in magnitude.

Skewness

 = 

3PM

STD3

 = 
1.28
3PM = Third upper moment
STD =   Standard Deviation of Sigma Lithium

Skewness Peers Comparison

The peer group averages -0.07 for Skewness, with Sigma Lithium at 1.28 falling above that level. Readings span -2.183 (Metallus) to 1.22 (American Battery Technology). Sigma Lithium's positive skew relative to peers indicates a higher frequency of large upside moves.

Skewness Relative To Other Indicators

The chart below plots Skewness against Maximum Drawdown for Sigma Lithium and its peers. Each point represents one equity — position along the horizontal axis shows Skewness 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.
The Maximum Drawdown-to-Skewness ratio for Sigma Lithium sits near 32.00 , with Skewness at 1.28 and Maximum Drawdown at 41.08 . This indicates Maximum Drawdown substantially exceeds Skewness for Sigma Lithium.
Compare Sigma Lithium to Peers

Methodology, Assumptions & Data Sources

The current Skewness for Sigma Lithium is 1.28. The Skewness for Sigma Lithium is produced by transforming raw price history into a standardized measure according to the indicator's defined methodology. 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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