$48.440
-0.368 (-0.76%)收盤時
價格預測
在 App 中開啟以解鎖更長週期的預測。
BP 相似圖表分析預測
Alphio's BP stock price prediction model matches the current BP PLC tape against historical breakout patterns, then publishes 1-day and 1-week targets first. The 1-day print is $46.87 (-3.25%). The 1-week path is $47.24 (-2.47%). 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 BP PLC 股票嗎?
BP PLC is a good buy right now due to its current price of $46.25, which is below the average analyst price target of $53.75, indicating potential upside. The stock has shown a strong year-to-date change of +29.08% and a 1-year change of +37.24%, reflecting solid momentum. The RSI is at 70.044, suggesting it is nearing overbought territory, but the overall trend remains positive. The main risk is the high debt-to-equity ratio of 95.12%, which could affect financial stability if market conditions worsen.
BP 股價於 Thursday 收在 $48.44,此前下跌 -0.76%
BP PLC (BP) last closed at $48.44, losing -0.76%. These facts feed the 1-day and 1-week BP price prediction above.
預測驅動因素
BP PLC(BP)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
Bullish
SMA 20
Bullish
SMA 200
Bullish
相似圖表形態
近期走勢與 BP 最接近的股票,依相似度排序。
BP 季節性分析
Historically the probability of a positive October return for BP is 59.65%. March offers the highest probability of a positive month at 100.00%, while November is the weakest seasonal window. Alphio blends this calendar with technical signals and similar chart pattern matching before it writes the forecast.
BP 十年價格預測
| 月份 | 最低價 | 平均價 | 最高價 | 潛在報酬率 |
|---|---|---|---|---|
| Oct 2026 | $24.30 | $24.46 | $26.30 | -49.50% |
| Nov 2026 | $28.67 | $30.96 | $32.46 | -36.09% |
| Dec 2026 | $23.87 | $27.29 | $28.21 | -43.66% |
2026 年,BP PLC(BP)預計區間為 $23.87 至 $32.46。
BP PLC 2026 年月度預測
2026 年 Oct,BP PLC 預計均價 $24.46,最低 $24.30,最高 $26.30。
2026 年 Nov,BP PLC 預計均價 $30.96,最低 $28.67,最高 $32.46。
2026 年 Dec,BP PLC 預計均價 $27.29,最低 $23.87,最高 $28.21。
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。