$3.380
+0.061 (+1.81%)收盤時
價格預測
在 App 中開啟以解鎖更長週期的預測。
LVO 相似圖表分析預測
Alphio's LVO stock price prediction model matches the current LiveOne Inc tape against historical breakout patterns, then publishes 1-day and 1-week targets first. The 1-day print is $3.50 (+3.55%). The 1-week path is $3.46 (+2.30%). 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 LiveOne Inc 股票嗎?
LiveOne Inc is not a strong buy right now due to its current price of $3.87, which is significantly below the analyst price target of $11. However, the company has reported a gross margin of 91.66% in the latest quarter, indicating strong profitability potential. The main risk is its negative net income, which was -7.6 million in Q4, reflecting ongoing financial challenges.
LVO 股價於 Thursday 收在 $3.38,此前上漲 +1.81%
LiveOne Inc (LVO) last closed at $3.38, gaining +1.81%. These facts feed the 1-day and 1-week LVO price prediction above.
預測驅動因素
LiveOne Inc(LVO)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
Bearish
SMA 20
Bearish
SMA 200
Bearish
相似圖表形態
近期走勢與 LVO 最接近的股票,依相似度排序。
LVO 季節性分析
Historically the probability of a positive September return for LVO is 31.82%. March offers the highest probability of a positive month at 66.67%, while October is the weakest seasonal window. Alphio blends this calendar with technical signals and similar chart pattern matching before it writes the forecast.
LVO 十年價格預測
| 月份 | 最低價 | 平均價 | 最高價 | 潛在報酬率 |
|---|---|---|---|---|
| Sep 2026 | $0.77 | $0.83 | $0.89 | -75.56% |
| Oct 2026 | $0.91 | $0.92 | $0.93 | -72.88% |
| Nov 2026 | $0.82 | $0.95 | $1.02 | -72.02% |
| Dec 2026 | $0.69 | $0.85 | $0.92 | -74.86% |
2026 年,LiveOne Inc(LVO)預計區間為 $0.69 至 $1.02。
LiveOne Inc 2026 年月度預測
2026 年 Sep,LiveOne Inc 預計均價 $0.83,最低 $0.77,最高 $0.89。
2026 年 Oct,LiveOne Inc 預計均價 $0.92,最低 $0.91,最高 $0.93。
2026 年 Nov,LiveOne Inc 預計均價 $0.95,最低 $0.82,最高 $1.02。
2026 年 Dec,LiveOne Inc 預計均價 $0.85,最低 $0.69,最高 $0.92。
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。