$16.030
+0.080 (+0.50%)收盤時
價格預測
在 App 中開啟以解鎖更長週期的預測。
ALKT 相似圖表分析預測
Alphio's ALKT stock price prediction model matches the current Alkami Technology, Inc. tape against historical breakout patterns, then publishes 1-day and 1-week targets first. The 1-day print is $16.12 (+0.57%). The 1-week path is $16.49 (+2.87%). 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 Alkami Technology, Inc. 股票嗎?
Alkami Technology Inc is not a good buy right now due to its current price of $13.73 being below analyst targets, with Barclays and JPMorgan setting targets at $15 and $14 respectively. Additionally, the RSI is at 34.219, indicating that the stock is oversold, but the overall trend is negative with a year-to-date change of -39.46%.
ALKT 股價於 Friday 收在 $16.03,此前上漲 +0.50%
Alkami Technology, Inc. (ALKT) last closed at $16.03, gaining +0.50%. These facts feed the 1-day and 1-week ALKT price prediction above.
預測驅動因素
Alkami Technology, Inc.(ALKT)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
Bullish
SMA 200
Bearish
相似圖表形態
近期走勢與 ALKT 最接近的股票,依相似度排序。
ALKT 季節性分析
Historically the probability of a positive October return for ALKT is 36.51%. November offers the highest probability of a positive month at 51.28%, while March is the weakest seasonal window. Alphio blends this calendar with technical signals and similar chart pattern matching before it writes the forecast.
ALKT 十年價格預測
| 月份 | 最低價 | 平均價 | 最高價 | 潛在報酬率 |
|---|---|---|---|---|
| Oct 2026 | $23.41 | $31.88 | $35.81 | +98.89% |
| Nov 2026 | $31.07 | $38.22 | $42.43 | +138.40% |
| Dec 2026 | $29.10 | $35.49 | $44.52 | +121.37% |
2026 年,Alkami Technology, Inc.(ALKT)預計區間為 $23.41 至 $44.52。
Alkami Technology, Inc. 2026 年月度預測
2026 年 Oct,Alkami Technology, Inc. 預計均價 $31.88,最低 $23.41,最高 $35.81。
2026 年 Nov,Alkami Technology, Inc. 預計均價 $38.22,最低 $31.07,最高 $42.43。
2026 年 Dec,Alkami Technology, Inc. 預計均價 $35.49,最低 $29.10,最高 $44.52。
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。