Equillium Inc

Equillium Inc(EQ)價格預測

$1.330

-0.067 (-5.00%)收盤時

價格預測

1-Day Price Prediction
+1.11%
1-Week Prediction
-3.28%
1-Month Prediction
—
2026 Prediction
—
2030 Prediction
—

在 App 中開啟以解鎖更長週期的預測。

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EQ 相似圖表分析預測

Alphio's EQ stock price prediction model matches the current Equillium Inc tape against historical breakout patterns, then publishes 1-day and 1-week targets first. The 1-day print is $1.34 (+1.11%). The 1-week path is $1.29 (-3.28%). 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 Equillium Inc 股票嗎?

Equillium Inc is a good buy right now due to its current price of $1.38, which is significantly below the analyst price targets of $20 and $6, indicating substantial upside potential. The RSI is at 53.339, suggesting a neutral momentum, while the stock has recently shown a 5-day change of +10.40%, indicating positive short-term performance. However, the main risk is the negative net income, with a loss of $5.3 million projected for Q1 2026, which investors should consider.

EQ 股價於 Thursday 收在 $1.33,此前下跌 -5.00%

Equillium Inc (EQ) last closed at $1.33, losing -5.00%. These facts feed the 1-day and 1-week EQ price prediction above.

分析師一致預期

Equillium Inc(EQ):買進 2、持有 0、賣出 0。展望:Strong Buy。

Technical signals summary based on buy and sell indicators. The gauge shows the overall market view.

Strong sellSellNeutralBuyStrong buy
Buy
Sell
0
Buy
2

預測驅動因素

Equillium Inc(EQ)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

Negative

Bearish

相似圖表形態

近期走勢與 EQ 最接近的股票,依相似度排序。

EQ 季節性分析

Historically the probability of a positive November return for EQ is 72.73%. September offers the highest probability of a positive month at 100.00%, while January is the weakest seasonal window. Alphio blends this calendar with technical signals and similar chart pattern matching before it writes the forecast.

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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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