CMB.TECH NV

CMB.TECH NV(CMBT)價格預測

$17.350

+0.101 (+0.58%)收盤時

價格預測

1-Day Price Prediction
+3.15%
1-Week Prediction
+4.58%
1-Month Prediction
—
2026 Prediction
—
2030 Prediction
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在 App 中開啟以解鎖更長週期的預測。

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CMBT 相似圖表分析預測

Alphio's CMBT stock price prediction model matches the current CMB.TECH NV tape against historical breakout patterns, then publishes 1-day and 1-week targets first. The 1-day print is $17.98 (+3.15%). The 1-week path is $18.23 (+4.58%). 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 CMB.TECH NV 股票嗎?

CMB.TECH NV is currently not a strong buy due to its recent price decline and technical indicators, despite a solid long-term outlook. The current price is $17.25, but the RSI is at a low 18.558, indicating oversold conditions. Additionally, the forward P/E ratio stands at 16.03, suggesting that the stock may be overvalued relative to its earnings potential. The recent 5-day change is a significant drop of -16.26%, which raises concerns about short-term performance. However, the company reported a net profit of $364.4 million in Q2, indicating strong operational performance. The primary risk is the recent price decline, which could continue if market sentiment does not improve.

CMBT 股價於 Monday 收在 $17.35,此前上漲 +0.58%

CMB.TECH NV (CMBT) last closed at $17.43, gaining +0.46%. These facts feed the 1-day and 1-week CMBT price prediction above.

預測驅動因素

CMB.TECH NV(CMBT)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

Positive

Bullish

Seasonality

Positive

Bullish

SMA 20

Negative

Bearish

SMA 200

Positive

Bullish

相似圖表形態

近期走勢與 CMBT 最接近的股票,依相似度排序。

CMBT 季節性分析

Historically the probability of a positive October return for CMBT is 61.67%. January offers the highest probability of a positive month at 88.52%, while December is the weakest seasonal window. Alphio blends this calendar with technical signals and similar chart pattern matching before it writes the forecast.

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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。

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