$8.680
-0.020 (-0.23%)At close
Price Predictions
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SAGE stock price ended at $8.68 on Wednesday, after losing -0.23%
SAGE Therapeutics Inc (SAGE) last closed at $8.68, losing -0.23%. These facts feed the 1-day and 1-week SAGE price prediction above.
Analyst Consensus
SAGE Therapeutics Inc (SAGE): 14 buy, 1 hold, 0 sell. Outlook: Strong Buy.
Sell / Buy
Technical signals summary based on buy and sell indicators. The gauge shows the overall market view.
Forecast Drivers
SAGE Therapeutics Inc (SAGE) forecast drivers combine similar chart patterns, seasonality, and moving averages.
Seasonality
Bearish
SMA 20
Bearish
SMA 200
Bullish
Seasonality analysis for SAGE
Historically the probability of a positive August return for SAGE is 0.00%. February offers the highest probability of a positive month at 87.18%, while August is the weakest seasonal window. Alphio blends this calendar with technical signals and similar chart pattern matching before it writes the forecast.
10-year price projections for SAGE
| Month | Min Price | Avg Price | Max Price | Potential ROI |
|---|---|---|---|---|
| Aug 2026 | $11.97 | $15.27 | $16.01 | +75.87% |
| Sep 2026 | $9.29 | $10.93 | $14.69 | +25.91% |
| Oct 2026 | $7.17 | $10.93 | $14.46 | +25.91% |
| Nov 2026 | $8.64 | $11.32 | $13.44 | +30.41% |
| Dec 2026 | $10.32 | $10.93 | $14.56 | +25.91% |
In 2026, SAGE Therapeutics Inc (SAGE) is projected to range from $7.17 to $16.01.
SAGE Therapeutics Inc 2026 monthly forecast
In Aug 2026, SAGE Therapeutics Inc is projected to average $15.27, with a low of $11.97 and high of $16.01.
In Sep 2026, SAGE Therapeutics Inc is projected to average $10.93, with a low of $9.29 and high of $14.69.
In Oct 2026, SAGE Therapeutics Inc is projected to average $10.93, with a low of $7.17 and high of $14.46.
In Nov 2026, SAGE Therapeutics Inc is projected to average $11.32, with a low of $8.64 and high of $13.44.
In Dec 2026, SAGE Therapeutics Inc is projected to average $10.93, with a low of $10.32 and high of $14.56.
This page is for research only and is not investment advice. Models can be wrong. Past performance does not guarantee future results.