$17.630
+0.130 (+0.74%)收盘时
价格预测
在 App 中打开以解锁更长周期的预测。
OSPN 相似图表分析预测
Alphio's OSPN stock price prediction model matches the current OneSpan Inc tape against historical breakout patterns, then publishes 1-day and 1-week targets first. The 1-day print is $18.21 (-0.20%). The 1-week path is $18.47 (+1.18%). 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 OneSpan Inc 股票吗?
OneSpan Inc (OSPN) is a good buy right now due to its current price of $17.50, which is below the analyst price target of $18. Additionally, the company reported a strong Q2 2026 with a 11% increase in subscription revenue and an adjusted EBITDA margin of 28%, indicating robust profitability. The main risk is the RSI at 39.446, suggesting the stock is nearing oversold territory, which could lead to further price declines in the short term.
OSPN 股价于 Monday 收于 $17.63,此前上涨 +0.74%
OneSpan Inc (OSPN) last closed at $18.25, gaining +3.52%. These facts feed the 1-day and 1-week OSPN price prediction above.
预测驱动因素
OneSpan Inc(OSPN)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
Bullish
SMA 200
Bullish
相似图表形态
近期走势与 OSPN 最接近的股票,按相似度排序。
OSPN 季节性分析
Historically the probability of a positive October return for OSPN is 61.67%. August offers the highest probability of a positive month at 67.19%, while March is the weakest seasonal window. Alphio blends this calendar with technical signals and similar chart pattern matching before it writes the forecast.
OSPN 十年价格预测
| 月份 | 最低价 | 平均价 | 最高价 | 潜在回报率 |
|---|---|---|---|---|
| Oct 2026 | $14.12 | $16.01 | $17.54 | -12.25% |
| Nov 2026 | $13.12 | $13.26 | $15.83 | -27.34% |
| Dec 2026 | $12.48 | $15.17 | $16.66 | -16.90% |
2026 年,OneSpan Inc(OSPN)预计区间为 $12.48 至 $17.54。
OneSpan Inc 2026 年月度预测
2026 年 Oct,OneSpan Inc 预计均价 $16.01,最低 $14.12,最高 $17.54。
2026 年 Nov,OneSpan Inc 预计均价 $13.26,最低 $13.12,最高 $15.83。
2026 年 Dec,OneSpan Inc 预计均价 $15.17,最低 $12.48,最高 $16.66。
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。