$4.380
-0.182 (-4.16%)收盘时
价格预测
在 App 中打开以解锁更长周期的预测。
FATN 相似图表分析预测
Alphio's FATN stock price prediction model matches the current FatPipe Inc tape against historical breakout patterns, then publishes 1-day and 1-week targets first. The 1-day print is $4.36 (-0.46%). The 1-week path is $4.55 (+3.99%). 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.
该买入 FatPipe Inc 股票吗?
FatPipe, Inc. appears to be a good buy right now due to its current price of $4.38, which is significantly below analyst price targets of $8 and $12, indicating potential upside of 82% to 174%. The company recently reported a Q4 revenue growth of 89.5% year-over-year and a net income of $4.0 million, showcasing strong financial performance. However, the RSI is low at 19.246, indicating potential oversold conditions, which could present a buying opportunity. The main risk is the recent 5-day change of -14.12%, reflecting volatility in the stock price.
FATN 股价于 Friday 收于 $4.38,此前下跌 -4.16%
FatPipe Inc (FATN) last closed at $4.3800001, losing -4.16%. These facts feed the 1-day and 1-week FATN price prediction above.
预测驱动因素
FatPipe Inc(FATN)的预测驱动因素综合了相似的图表形态、季节性与移动平均线。
Similar patterns
Bullish
Seasonality
Bearish
SMA 20
Bearish
SMA 200
Bullish
相似图表形态
近期走势与 FATN 最接近的股票,按相似度排序。
FATN 季节性分析
Historically the probability of a positive November return for FATN is 20.83%. June offers the highest probability of a positive month at 51.22%, while December is the weakest seasonal window. Alphio blends this calendar with technical signals and similar chart pattern matching before it writes the forecast.
FATN 十年价格预测
| 月份 | 最低价 | 平均价 | 最高价 | 潜在回报率 |
|---|---|---|---|---|
| Nov 2026 | $8.32 | $9.85 | $11.09 | +124.96% |
| Dec 2026 | $7.56 | $8.83 | $10.50 | +101.63% |
2026 年,FatPipe Inc(FATN)预计区间为 $7.56 至 $11.09。
FatPipe Inc 2026 年月度预测
2026 年 Nov,FatPipe Inc 预计均价 $9.85,最低 $8.32,最高 $11.09。
2026 年 Dec,FatPipe Inc 预计均价 $8.83,最低 $7.56,最高 $10.50。
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本页仅供研究参考,不构成投资建议。模型可能出错。过往表现不代表未来结果。