$9.110
-0.243 (-2.67%)收盘时
价格预测
在 App 中打开以解锁更长周期的预测。
PHAR 相似图表分析预测
Alphio's PHAR stock price prediction model matches the current Pharming Group NV tape against historical breakout patterns, then publishes 1-day and 1-week targets first. The 1-day print is $9.72 (-0.32%). The 1-week path is $9.76 (+0.07%). 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 Pharming Group NV 股票吗?
Pharming Group NV is not a good buy right now due to its current price of $9.36, which is significantly below the analyst price target range of $37 to $40. Additionally, the stock has a high forward P/E ratio of 212.77, indicating overvaluation concerns. The RSI is at 30.07, suggesting the stock is oversold, but this could indicate further downside risk rather than an immediate buying opportunity.
PHAR 股价于 Monday 收于 $9.11,此前下跌 -2.67%
Pharming Group NV (PHAR) last closed at $9.75, gaining +7.03%. These facts feed the 1-day and 1-week PHAR price prediction above.
预测驱动因素
Pharming Group NV(PHAR)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
Bearish
相似图表形态
近期走势与 PHAR 最接近的股票,按相似度排序。
PHAR 季节性分析
Historically the probability of a positive October return for PHAR is 38.33%. January offers the highest probability of a positive month at 59.02%, while March is the weakest seasonal window. Alphio blends this calendar with technical signals and similar chart pattern matching before it writes the forecast.
PHAR 十年价格预测
| 月份 | 最低价 | 平均价 | 最高价 | 潜在回报率 |
|---|---|---|---|---|
| Oct 2026 | $10.21 | $10.37 | $13.00 | +6.32% |
| Nov 2026 | $11.69 | $11.94 | $11.95 | +22.41% |
| Dec 2026 | $9.43 | $10.15 | $11.40 | +4.08% |
2026 年,Pharming Group NV(PHAR)预计区间为 $9.43 至 $13.00。
Pharming Group NV 2026 年月度预测
2026 年 Oct,Pharming Group NV 预计均价 $10.37,最低 $10.21,最高 $13.00。
2026 年 Nov,Pharming Group NV 预计均价 $11.94,最低 $11.69,最高 $11.95。
2026 年 Dec,Pharming Group NV 预计均价 $10.15,最低 $9.43,最高 $11.40。
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。