$1.790
+0.084 (+4.68%)收盤時
價格預測
在 App 中開啟以解鎖更長週期的預測。
LGVN 相似圖表分析預測
Alphio's LGVN stock price prediction model matches the current Longeveron Inc tape against historical breakout patterns, then publishes 1-day and 1-week targets first. The 1-day print is $1.78 (-0.43%). The 1-week path is $1.80 (+0.63%). 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.
該買進 Longeveron Inc 股票嗎?
Longeveron Inc. is currently not a strong buy due to its ongoing financial struggles and recent trial failures. The stock is trading at $1.79, which is significantly lower than its 52-week high of $12.30, indicating a substantial decline of 85.4%. Additionally, the company reported a gross margin of 66.33% in Q1 2026, but its net income remains deeply negative, with a net margin of -1189.95% in Q1 2026. The recent failure of the ELPIS II trial raises concerns about future growth and financing opportunities, making it a risky investment at this time.
LGVN 股價於 Friday 收在 $1.79,此前上漲 +4.68%
Longeveron Inc (LGVN) last closed at $1.79, gaining +4.68%. These facts feed the 1-day and 1-week LGVN price prediction above.
預測驅動因素
Longeveron Inc(LGVN)的預測驅動因素綜合了相似的圖表形態、季節性與移動平均線。
Similar patterns
Bullish
Seasonality
Bearish
SMA 20
Bullish
SMA 200
Bearish
相似圖表形態
近期走勢與 LGVN 最接近的股票,依相似度排序。
LGVN 季節性分析
Historically the probability of a positive November return for LGVN is 0.00%. June offers the highest probability of a positive month at 35.00%, while February is the weakest seasonal window. Alphio blends this calendar with technical signals and similar chart pattern matching before it writes the forecast.
LGVN 十年價格預測
| 月份 | 最低價 | 平均價 | 最高價 | 潛在報酬率 |
|---|---|---|---|---|
| Nov 2026 | $2.86 | $3.08 | $3.14 | +72.02% |
| Dec 2026 | $3.60 | $3.87 | $4.46 | +115.98% |
2026 年,Longeveron Inc(LGVN)預計區間為 $2.86 至 $4.46。
Longeveron Inc 2026 年月度預測
2026 年 Nov,Longeveron Inc 預計均價 $3.08,最低 $2.86,最高 $3.14。
2026 年 Dec,Longeveron Inc 預計均價 $3.87,最低 $3.60,最高 $4.46。
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本頁僅供研究參考,不構成投資建議。模型可能出錯。過往表現不代表未來結果。