Quantum Biopharma Ltd（QNTM）价格预测

$2.090

-0.020 (-0.95%)收盘时

价格预测

1-Day Price Prediction

+0.28%

1-Week Prediction

+2.37%

1-Month Prediction

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2026 Prediction

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2030 Prediction

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在 App 中打开以解锁更长周期的预测。

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QNTM 相似图表分析预测

Alphio's QNTM stock price prediction model matches the current Quantum Biopharma Ltd tape against historical breakout patterns, then publishes 1-day and 1-week targets first. The 1-day print is $2.10 (+0.28%). The 1-week path is $2.14 (+2.37%). 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 Quantum Biopharma Ltd 股票吗？

Quantum BioPharma Ltd (QNTM) is not a good buy right now due to its significant financial losses and declining stock performance. The current price is $2.09, which is 75.09% lower than its 1-year high of $12.42. The company has a negative gross profit of -129298 USD for Q1 2025 and a forward P/E of 0, indicating no expected earnings growth. Additionally, the RSI is at a very low 20.861, suggesting oversold conditions but also a lack of upward momentum. The main risk is the 70.19% year-to-date decline, which indicates ongoing challenges in the company's financial health and market perception.

QNTM 股价于 Friday 收于 $2.09，此前下跌 -0.95%

Quantum Biopharma Ltd (QNTM) last closed at $2.0899999, losing -0.95%. These facts feed the 1-day and 1-week QNTM price prediction above.

预测驱动因素

Quantum Biopharma Ltd（QNTM）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

Positive

Bullish

Seasonality

Negative

Bearish

SMA 20

Negative

Bearish

SMA 200

Negative

Bearish

相似图表形态

近期走势与 QNTM 最接近的股票，按相似度排序。

TOL

92.33%

-10.74%

ITW

91.58%

+8.20%

CUBE

91.23%

-3.56%

COR

90.93%

-18.62%

SMPL

90.69%

-11.75%

QNTM 季节性分析

Historically the probability of a positive November return for QNTM is 43.18%. December offers the highest probability of a positive month at 51.16%, while January 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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