The average one-year price target for Sigma Lithium (NasdaqCM:SGML) has been revised to $7.82 / share. This is an increase of 14.97% from the prior estimate of $6.80 dated December 5, 2025. The price ...

Sigma Lithium (SGML) has quietly outperformed many battery-material peers lately, with the stock up around 37% over the past month and more than doubling in the past 3 months. See our latest analysis ...

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Recent reports of tighter lithium supply from China have pushed prices higher, with Sigma Lithium responding by adjusting sales volumes to benefit from the stronger pricing environment and support ...

) has been revised to $7.82 / share. This is an increase of 14.97% from the prior estimate of $6.80 dated December 5, 2025. The price target is an average of many targets provided by analysts. The ...

Sigma Lithium Corporation (SGML) related ETFs: find ETFs with exposure to Sigma Lithium Corporation (SGML). Discover ETFs with positive and negative correlation to Sigma Lithium Corporation (SGML).

Fears of a tighter lithium supply from China are driving up prices. Sigma Lithium could greatly benefit as it adjusts sales volumes to capitalize on higher prices. The lithium stock is up only about ...

China is canceling old lithium mining licenses, mostly for non-operational mines. Chinese lithium prices spiked on the news, pushing lithium stocks higher today. The Bureau of Natural Resources in ...

The Price to Earnings (P/E) ratio, a key valuation measure, is calculated by dividing the stock's most recent closing price by the sum of the diluted earnings per share from continuing operations for ...

Wednesday’s market has seen swings in various stocks based on news and other factors. Today, stocks like Avago Technologies and... Wednesday’s market has seen swings in various stocks based on news ...

Lithium prices touched 18-month highs this week. A major Chinese lithium miner projects exponential growth in the demand and prices of lithium in 2026. Sigma Lithium is rapidly expanding its capacity ...

Abstract: Recently, the semi-supervised graph convolutional network (SSGCN) has been verified effective for hyperspectral image (HSI) classification. However, constrained by the limited training data ...