$9.840
-0.010 (-0.10%)收盤時
價格預測
在 App 中開啟以解鎖更長週期的預測。
SHOT 相似圖表分析預測
Alphio's SHOT stock price prediction model matches the current Bonk Inc tape against historical breakout patterns, then publishes 1-day and 1-week targets first. The 1-day print is $9.82 (-0.16%). The 1-week path is $9.79 (-0.47%). 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 Bonk Inc 股票嗎?
Safety Shot Inc is a good buy right now due to its recent strategic partnership that led to a 12% rise in after-hours trading, and a remarkable 1-year change of 2097.41%. The current price of $9.84 is well below the projected price targets, indicating potential for growth. However, the company has shown volatility with a high historical volatility of 129.01%, which could pose risks for investors.
SHOT 股價於 Tuesday 收在 $9.84,此前下跌 -0.10%
Bonk Inc (SHOT) last closed at $9.84, losing -0.10%. These facts feed the 1-day and 1-week SHOT price prediction above.
預測驅動因素
Bonk Inc(SHOT)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
Bullish
SMA 200
Bullish
相似圖表形態
近期走勢與 SHOT 最接近的股票,依相似度排序。
SHOT 季節性分析
Historically the probability of a positive September return for SHOT is 2.38%. August offers the highest probability of a positive month at 32.81%, while March is the weakest seasonal window. Alphio blends this calendar with technical signals and similar chart pattern matching before it writes the forecast.
SHOT 十年價格預測
| 月份 | 最低價 | 平均價 | 最高價 | 潛在報酬率 |
|---|---|---|---|---|
| Sep 2026 | $0.50 | $0.52 | $0.55 | -94.75% |
| Oct 2026 | $0.44 | $0.54 | $0.63 | -94.55% |
| Nov 2026 | $0.53 | $0.61 | $0.70 | -93.80% |
| Dec 2026 | $0.41 | $0.49 | $0.54 | -95.01% |
2026 年,Bonk Inc(SHOT)預計區間為 $0.41 至 $0.70。
Bonk Inc 2026 年月度預測
2026 年 Sep,Bonk Inc 預計均價 $0.52,最低 $0.50,最高 $0.55。
2026 年 Oct,Bonk Inc 預計均價 $0.54,最低 $0.44,最高 $0.63。
2026 年 Nov,Bonk Inc 預計均價 $0.61,最低 $0.53,最高 $0.70。
2026 年 Dec,Bonk Inc 預計均價 $0.49,最低 $0.41,最高 $0.54。
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。