$2.270
-0.086 (-3.81%)At close
Price Predictions
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CMCM Prediction & Forecast by Similar Chart Analysis
Alphio's CMCM stock price prediction model matches the current Cheetah Mobile Inc tape against historical breakout patterns, then publishes 1-day and 1-week targets first. The 1-day print is $2.30 (+1.29%). The 1-week path is $2.24 (-1.32%). Longer windows use the same pattern set plus seasonality; the 1-month and multi-year forecasts sit behind unlock because they include precise min / avg / max bands.
Should I Buy Cheetah Mobile Inc Stock?
Cheetah Mobile Inc (CMCM) is currently priced at $2.46, which is significantly lower than its 52-week high of $9.00, indicating potential upside. However, the company has reported a net income loss of -$94.91 million in Q2 2026, and its gross margin has declined to 63.37%. The stock's RSI is at 54.40, suggesting it is neither overbought nor oversold, which indicates a wait-and-see approach is prudent.
CMCM stock price ended at $2.27 on Thursday, after losing -3.81%
Cheetah Mobile Inc (CMCM) last closed at $2.27, losing -3.81%. These facts feed the 1-day and 1-week CMCM price prediction above.
Analyst Consensus
Cheetah Mobile Inc (CMCM): 0 buy, 6 hold, 0 sell. Outlook: Hold.
Sell / Buy
Technical signals summary based on buy and sell indicators. The gauge shows the overall market view.
Forecast Drivers
Cheetah Mobile Inc (CMCM) forecast drivers combine similar chart patterns, seasonality, and moving averages.
Similar patterns
Bullish
Seasonality
Bullish
SMA 20
Bearish
SMA 200
Bearish
Similar Chart Patterns
Stocks whose recent price path most closely matches CMCM, ranked by similarity.
Seasonality analysis for CMCM
Historically the probability of a positive November return for CMCM is 88.64%. December offers the highest probability of a positive month at 100.00%, while June is the weakest seasonal window. Alphio blends this calendar with technical signals and similar chart pattern matching before it writes the forecast.
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This page is for research only and is not investment advice. Models can be wrong. Past performance does not guarantee future results.