$697.520
+3.278 (+0.47%)收盘时
价格预测
在 App 中打开以解锁更长周期的预测。
META 相似图表分析预测
Alphio's META stock price prediction model matches the current Meta Platforms Inc tape against historical breakout patterns, then publishes 1-day and 1-week targets first. The 1-day print is $649.89 (+0.16%). The 1-week path is $667.47 (+2.87%). 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 Meta Platforms Inc 股票吗？
Meta Platforms Inc is a good buy right now, trading at $709.33 with a forward P/E of 22.08, indicating potential for growth. The gross margin stands at 81.37%, reflecting strong profitability. The main risk is the recent decline in the stock price, which has dropped 3.72% in the last day and 1.30% over the past week, suggesting some volatility ahead.
META 股价于 Wednesday 收于 $697.52，此前上涨 +0.47%
Meta Platforms Inc (META) last closed at $648.85, losing -6.98%. These facts feed the 1-day and 1-week META price prediction above.
预测驱动因素
Meta Platforms Inc（META）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
Bearish
SMA 200
Bullish
相似图表形态
近期走势与 META 最接近的股票，按相似度排序。
META 季节性分析
Historically the probability of a positive October return for META is 98.39%. December offers the highest probability of a positive month at 100.00%, while April is the weakest seasonal window. Alphio blends this calendar with technical signals and similar chart pattern matching before it writes the forecast.
META 十年价格预测
| 月份 | 最低价 | 平均价 | 最高价 | 潜在回报率 |
|---|---|---|---|---|
| Oct 2026 | $828.59 | $868.88 | $940.24 | +33.91% |
| Nov 2026 | $739.32 | $868.88 | $1,009.44 | +33.91% |
| Dec 2026 | $854.89 | $868.88 | $1,026.87 | +33.91% |
2026 年，Meta Platforms Inc（META）预计区间为 $739.32 至 $1026.87。
Meta Platforms Inc 2026 年月度预测
2026 年 Oct，Meta Platforms Inc 预计均价 $868.88，最低 $828.59，最高 $940.24。
2026 年 Nov，Meta Platforms Inc 预计均价 $868.88，最低 $739.32，最高 $1,009.44。
2026 年 Dec，Meta Platforms Inc 预计均价 $868.88，最低 $854.89，最高 $1,026.87。
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。