$10.560
+0.010 (+0.09%)收盤時
價格預測
在 App 中開啟以解鎖更長週期的預測。
TACH 相似圖表分析預測
Alphio's TACH stock price prediction model matches the current Titan Acquisition Corp tape against historical breakout patterns, then publishes 1-day and 1-week targets first. The 1-day print is $10.59 (+0.22%). The 1-week path is $10.94 (+3.50%). 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 Titan Acquisition Corp 股票嗎?
Titan Acquisition Corp is a good buy right now due to its recent positive earnings momentum, with a projected EPS of 0.22 in Q3 2025, and a current price of 10.55, which is near key Fibonacci resistance levels. The RSI is at 82.92, indicating strong momentum, but caution is warranted as the high RSI suggests potential overbought conditions.
TACH 股價於 Monday 收在 $10.56,此前上漲 +0.09%
Titan Acquisition Corp (TACH) last closed at $10.5699997, gaining +0.19%. These facts feed the 1-day and 1-week TACH price prediction above.
預測驅動因素
Titan Acquisition Corp(TACH)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
Bullish
SMA 20
Bullish
SMA 200
Bullish
相似圖表形態
近期走勢與 TACH 最接近的股票,依相似度排序。
TACH 季節性分析
Historically the probability of a positive October return for TACH is 100.00%. February offers the highest probability of a positive month at 100.00%, while May is the weakest seasonal window. Alphio blends this calendar with technical signals and similar chart pattern matching before it writes the forecast.
TACH 十年價格預測
| 月份 | 最低價 | 平均價 | 最高價 | 潛在報酬率 |
|---|---|---|---|---|
| Oct 2026 | $11.63 | $12.03 | $12.40 | +13.81% |
| Nov 2026 | $10.47 | $12.16 | $12.92 | +15.04% |
| Dec 2026 | $7.71 | $8.99 | $11.36 | -14.97% |
2026 年,Titan Acquisition Corp(TACH)預計區間為 $7.71 至 $12.92。
Titan Acquisition Corp 2026 年月度預測
2026 年 Oct,Titan Acquisition Corp 預計均價 $12.03,最低 $11.63,最高 $12.40。
2026 年 Nov,Titan Acquisition Corp 預計均價 $12.16,最低 $10.47,最高 $12.92。
2026 年 Dec,Titan Acquisition Corp 預計均價 $8.99,最低 $7.71,最高 $11.36。
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。