$36.380
+0.029 (+0.08%)At close
Price Predictions
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SEPN Prediction & Forecast by Similar Chart Analysis
Alphio's SEPN stock price prediction model matches the current Septerna Inc tape against historical breakout patterns, then publishes 1-day and 1-week targets first. The 1-day print is $36.02 (-1.00%). The 1-week path is $37.23 (+2.33%). 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 Septerna Inc Stock?
Currently, Septerna Inc is not a strong buy due to its recent price decline and mixed financial performance. The current price is $36.35, and the RSI is at 41.302, indicating it is nearing oversold territory but not yet a strong buy signal. The forward P/E ratio is notably high at 107.53, suggesting that the stock may be overvalued relative to its earnings potential. Additionally, the stock has seen a 5-day change of -5.26% and a 20-day change of -6.05%, reflecting recent downward momentum. The main risk is the high forward P/E ratio, which indicates potential overvaluation if future earnings do not meet expectations.
SEPN stock price ended at $36.38 on Monday, after rising +0.08%
Septerna Inc (SEPN) last closed at $36.38, gaining +0.08%. These facts feed the 1-day and 1-week SEPN price prediction above.
Forecast Drivers
Septerna Inc (SEPN) forecast drivers combine similar chart patterns, seasonality, and moving averages.
Similar patterns
Bullish
Seasonality
Bullish
SMA 20
Bearish
SMA 200
Bullish
Similar Chart Patterns
Stocks whose recent price path most closely matches SEPN, ranked by similarity.
Seasonality analysis for SEPN
Historically the probability of a positive October return for SEPN is 73.81%. December offers the highest probability of a positive month at 100.00%, while April is the weakest seasonal window. Alphio blends this calendar with technical signals and similar chart pattern matching before it writes the forecast.
This page is for research only and is not investment advice. Models can be wrong. Past performance does not guarantee future results.