$1.470
+0.409 (+27.83%)收盘时
价格预测
在 App 中打开以解锁更长周期的预测。
LIDR 相似图表分析预测
Alphio's LIDR stock price prediction model matches the current AEye Inc tape against historical breakout patterns, then publishes 1-day and 1-week targets first. The 1-day print is $1.54 (+4.46%). The 1-week path is $1.48 (+0.99%). 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 AEye Inc 股票吗?
AEye Inc (LIDR) appears to be a good buy right now due to its current price of $1.15, which is significantly below the analyst price target of $3.50. The company has shown a 60% increase in revenue from Q1 2025 to Q1 2026, indicating strong growth potential. However, the main risk is the negative earnings per share (EPS) of -0.22 reported in Q2 2026, which reflects ongoing financial challenges.
LIDR 股价于 Tuesday 收于 $1.47,此前上涨 +27.83%
AEye Inc (LIDR) last closed at $1.47, gaining +27.83%. These facts feed the 1-day and 1-week LIDR price prediction above.
预测驱动因素
AEye Inc(LIDR)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
Bullish
Seasonality
Bullish
SMA 20
Bullish
SMA 200
Bearish
相似图表形态
近期走势与 LIDR 最接近的股票,按相似度排序。
LIDR 季节性分析
Historically the probability of a positive September return for LIDR is 50.00%. December offers the highest probability of a positive month at 51.16%, while February is the weakest seasonal window. Alphio blends this calendar with technical signals and similar chart pattern matching before it writes the forecast.
LIDR 十年价格预测
| 月份 | 最低价 | 平均价 | 最高价 | 潜在回报率 |
|---|---|---|---|---|
| Sep 2026 | $0.46 | $0.57 | $0.66 | -60.97% |
| Oct 2026 | $0.34 | $0.35 | $0.37 | -75.95% |
| Nov 2026 | $0.20 | $0.40 | $0.42 | -72.49% |
| Dec 2026 | $0.11 | $0.35 | $0.45 | -75.95% |
2026 年,AEye Inc(LIDR)预计区间为 $0.11 至 $0.66。
AEye Inc 2026 年月度预测
2026 年 Sep,AEye Inc 预计均价 $0.57,最低 $0.46,最高 $0.66。
2026 年 Oct,AEye Inc 预计均价 $0.35,最低 $0.34,最高 $0.37。
2026 年 Nov,AEye Inc 预计均价 $0.40,最低 $0.20,最高 $0.42。
2026 年 Dec,AEye Inc 预计均价 $0.35,最低 $0.11,最高 $0.45。
本页仅供研究参考,不构成投资建议。模型可能出错。过往表现不代表未来结果。