$3.810
-0.265 (-6.96%)收盘时
价格预测
在 App 中打开以解锁更长周期的预测。
ARKO 相似图表分析预测
Alphio's ARKO stock price prediction model matches the current Arko Corp. tape against historical breakout patterns, then publishes 1-day and 1-week targets first. The 1-day print is $3.81 (+0.05%). The 1-week path is $3.75 (-1.53%). 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 Arko Corp. 股票吗?
Arko Corp. is not a strong buy at this moment due to its low current price of $3.81 and an RSI of 24.83, indicating oversold conditions. The stock's recent performance has been poor, with a 5-day change of -7.07% and a year-to-date change of -14.77%. However, the stock is considered inexpensive at current levels, suggesting potential for recovery. The main risk is the company's negative net income of $8,059,000 in Q1 2026, which raises concerns about its financial health.
ARKO 股价于 Friday 收于 $3.81,此前下跌 -6.96%
Arko Corp. (ARKO) last closed at $3.81, losing -6.96%. These facts feed the 1-day and 1-week ARKO price prediction above.
预测驱动因素
Arko Corp.(ARKO)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 ARKO 最接近的股票,按相似度排序。
ARKO 季节性分析
Historically the probability of a positive October return for ARKO is 0.00%. February offers the highest probability of a positive month at 63.79%, while October is the weakest seasonal window. Alphio blends this calendar with technical signals and similar chart pattern matching before it writes the forecast.
ARKO 十年价格预测
| 月份 | 最低价 | 平均价 | 最高价 | 潜在回报率 |
|---|---|---|---|---|
| Oct 2026 | $3.55 | $3.58 | $3.82 | -5.97% |
| Nov 2026 | $2.81 | $3.43 | $4.07 | -9.89% |
| Dec 2026 | $3.63 | $3.91 | $4.51 | +2.69% |
2026 年,Arko Corp.(ARKO)预计区间为 $2.81 至 $4.51。
Arko Corp. 2026 年月度预测
2026 年 Oct,Arko Corp. 预计均价 $3.58,最低 $3.55,最高 $3.82。
2026 年 Nov,Arko Corp. 预计均价 $3.43,最低 $2.81,最高 $4.07。
2026 年 Dec,Arko Corp. 预计均价 $3.91,最低 $3.63,最高 $4.51。
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。