$41.610
+1.731 (+4.16%)收盤時
價格預測
在 App 中開啟以解鎖更長週期的預測。
MP 相似圖表分析預測
Alphio's MP stock price prediction model matches the current MP Materials Corp tape against historical breakout patterns, then publishes 1-day and 1-week targets first. The 1-day print is $40.97 (+2.00%). The 1-week path is $43.52 (+8.35%). 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 MP Materials Corp 股票嗎?
Given the current price of $46.14 and the downward revisions of analyst price targets, MP Materials Corp is not a good buy right now. The stock has a low RSI of 39.46, indicating it is oversold, but the significant 1-year change of -51.46% and negative earnings reports suggest further declines could occur. The main risk is the forward P/E ratio of 47.39, which indicates high valuation despite poor earnings performance.
MP 股價於 Thursday 收在 $41.61,此前上漲 +4.16%
MP Materials Corp (MP) last closed at $40.17, losing -3.46%. These facts feed the 1-day and 1-week MP price prediction above.
預測驅動因素
MP Materials Corp(MP)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 MP 最接近的股票,依相似度排序。
MP 季節性分析
Historically the probability of a positive October return for MP is 39.66%. November offers the highest probability of a positive month at 69.23%, while July is the weakest seasonal window. Alphio blends this calendar with technical signals and similar chart pattern matching before it writes the forecast.
MP 十年價格預測
| 月份 | 最低價 | 平均價 | 最高價 | 潛在報酬率 |
|---|---|---|---|---|
| Oct 2026 | $23.53 | $23.78 | $29.74 | -40.80% |
| Nov 2026 | $32.88 | $33.03 | $35.38 | -17.77% |
| Dec 2026 | $26.36 | $29.35 | $38.29 | -26.95% |
2026 年,MP Materials Corp(MP)預計區間為 $23.53 至 $38.29。
MP Materials Corp 2026 年月度預測
2026 年 Oct,MP Materials Corp 預計均價 $23.78,最低 $23.53,最高 $29.74。
2026 年 Nov,MP Materials Corp 預計均價 $33.03,最低 $32.88,最高 $35.38。
2026 年 Dec,MP Materials Corp 預計均價 $29.35,最低 $26.36,最高 $38.29。
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。