$13.440
-0.079 (-0.59%)收盘时
价格预测
在 App 中打开以解锁更长周期的预测。
DOLE 相似图表分析预测
Alphio's DOLE stock price prediction model matches the current Dole PLC tape against historical breakout patterns, then publishes 1-day and 1-week targets first. The 1-day print is $13.65 (+1.55%). The 1-week path is $13.97 (+3.95%). 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 Dole PLC 股票吗?
Dole PLC is currently trading at $13.44, which is below the analyst price target of $14, suggesting limited upside potential. The forward P/E ratio of 8.489 indicates that the stock is relatively undervalued compared to its earnings potential. However, the stock has a year-to-date change of -8.13%, which raises concerns about its recent performance. The main risk is the negative earnings surprise of -8% in the last quarter, which could impact investor sentiment.
DOLE 股价于 Friday 收于 $13.44,此前下跌 -0.59%
Dole PLC (DOLE) last closed at $13.44, losing -0.59%. These facts feed the 1-day and 1-week DOLE price prediction above.
预测驱动因素
Dole PLC(DOLE)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
Bullish
SMA 200
Bearish
相似图表形态
近期走势与 DOLE 最接近的股票,按相似度排序。
DOLE 季节性分析
Historically the probability of a positive October return for DOLE is 36.51%. December offers the highest probability of a positive month at 100.00%, while January is the weakest seasonal window. Alphio blends this calendar with technical signals and similar chart pattern matching before it writes the forecast.
DOLE 十年价格预测
| 月份 | 最低价 | 平均价 | 最高价 | 潜在回报率 |
|---|---|---|---|---|
| Oct 2026 | $11.75 | $13.61 | $16.90 | +1.26% |
| Nov 2026 | $15.48 | $15.91 | $17.52 | +18.39% |
| Dec 2026 | $14.46 | $14.67 | $17.34 | +9.19% |
2026 年,Dole PLC(DOLE)预计区间为 $11.75 至 $17.52。
Dole PLC 2026 年月度预测
2026 年 Oct,Dole PLC 预计均价 $13.61,最低 $11.75,最高 $16.90。
2026 年 Nov,Dole PLC 预计均价 $15.91,最低 $15.48,最高 $17.52。
2026 年 Dec,Dole PLC 预计均价 $14.67,最低 $14.46,最高 $17.34。
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。