$5.065
+0.097 (+1.91%)收盤時
價格預測
在 App 中開啟以解鎖更長週期的預測。
HNST 相似圖表分析預測
Alphio's HNST stock price prediction model matches the current Honest Company Inc tape against historical breakout patterns, then publishes 1-day and 1-week targets first. The 1-day print is $4.86 (-0.06%). The 1-week path is $4.77 (-1.84%). 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 Honest Company Inc 股票嗎?
The Honest Company is currently priced at $5, which is at the lower end of analyst price targets that range from $5 to $5.50. The company has shown a significant year-to-date change of +91.57%, but its recent RSI of 38.32 indicates it may be oversold. The main risk is the declining revenue growth, which has been only 5.8% annually over the past three years, raising concerns about future performance.
HNST 股價於 Tuesday 收在 $5.07,此前上漲 +1.91%
Honest Company Inc (HNST) last closed at $4.86, losing -4.05%. These facts feed the 1-day and 1-week HNST price prediction above.
預測驅動因素
Honest Company Inc(HNST)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
Bearish
SMA 200
Bullish
相似圖表形態
近期走勢與 HNST 最接近的股票,依相似度排序。
HNST 季節性分析
Historically the probability of a positive October return for HNST is 62.30%. September offers the highest probability of a positive month at 66.13%, while January is the weakest seasonal window. Alphio blends this calendar with technical signals and similar chart pattern matching before it writes the forecast.
HNST 十年價格預測
| 月份 | 最低價 | 平均價 | 最高價 | 潛在報酬率 |
|---|---|---|---|---|
| Oct 2026 | $5.98 | $6.08 | $6.44 | +25.09% |
| Nov 2026 | $5.35 | $5.69 | $6.39 | +17.12% |
| Dec 2026 | $4.32 | $5.28 | $5.61 | +8.72% |
2026 年,Honest Company Inc(HNST)預計區間為 $4.32 至 $6.44。
Honest Company Inc 2026 年月度預測
2026 年 Oct,Honest Company Inc 預計均價 $6.08,最低 $5.98,最高 $6.44。
2026 年 Nov,Honest Company Inc 預計均價 $5.69,最低 $5.35,最高 $6.39。
2026 年 Dec,Honest Company Inc 預計均價 $5.28,最低 $4.32,最高 $5.61。
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。