$0.406
-0.040 (-9.93%)收盤時
價格預測
在 App 中開啟以解鎖更長週期的預測。
EPOW 相似圖表分析預測
Alphio's EPOW stock price prediction model matches the current E-Power Inc tape against historical breakout patterns, then publishes 1-day and 1-week targets first. The 1-day print is $0.40 (-2.21%). The 1-week path is $0.40 (-1.98%). 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 E-Power Inc 股票嗎?
EPOW is a good buy right now due to its recent contract worth $51.1 million, indicating strong revenue potential, and a 5-day price increase of 11.58%, suggesting positive momentum. However, the stock is currently trading at $0.50, which is below the $1.00 compliance threshold set by Nasdaq, posing a risk of delisting if not addressed within the compliance period.
EPOW 股價於 Wednesday 收在 $0.41,此前下跌 -9.93%
E-Power Inc (EPOW) last closed at $0.4062, losing -9.93%. These facts feed the 1-day and 1-week EPOW price prediction above.
預測驅動因素
E-Power Inc(EPOW)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
Bearish
SMA 200
Bearish
相似圖表形態
近期走勢與 EPOW 最接近的股票,依相似度排序。
EPOW 季節性分析
Historically the probability of a positive September return for EPOW is 41.86%. October offers the highest probability of a positive month at 50.00%, while January is the weakest seasonal window. Alphio blends this calendar with technical signals and similar chart pattern matching before it writes the forecast.
EPOW 十年價格預測
| 月份 | 最低價 | 平均價 | 最高價 | 潛在報酬率 |
|---|---|---|---|---|
| Sep 2026 | $0.89 | $0.98 | $1.09 | +141.19% |
| Oct 2026 | $0.83 | $0.90 | $0.99 | +122.00% |
| Nov 2026 | $0.68 | $0.82 | $0.89 | +101.16% |
| Dec 2026 | $0.92 | $0.97 | $1.03 | +138.49% |
2026 年,E-Power Inc(EPOW)預計區間為 $0.68 至 $1.09。
E-Power Inc 2026 年月度預測
2026 年 Sep,E-Power Inc 預計均價 $0.98,最低 $0.89,最高 $1.09。
2026 年 Oct,E-Power Inc 預計均價 $0.90,最低 $0.83,最高 $0.99。
2026 年 Nov,E-Power Inc 預計均價 $0.82,最低 $0.68,最高 $0.89。
2026 年 Dec,E-Power Inc 預計均價 $0.97,最低 $0.92,最高 $1.03。
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。