$20.940
-0.109 (-0.52%)終値時点
価格予想
アプリで開くと、より長期の予想を確認できます。
類似チャート分析による INVA の予測・予想
Alphio's INVA stock price prediction model matches the current Innoviva Inc tape against historical breakout patterns, then publishes 1-day and 1-week targets first. The 1-day print is $21.34 (+1.06%). The 1-week path is $21.31 (+0.92%). 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.
Innoviva Inc 株は買うべき?
Innoviva Inc is a good buy right now due to its current price of $20.66, which is significantly lower than the analyst price targets of $34 to $42. The stock has a low forward P/E ratio of 8.54, indicating it may be undervalued compared to its earnings potential. However, investors should be cautious of the recent Q2 loss of $83.4 million, which reflects ongoing profitability challenges.
INVA の株価は Tuesday に $20.94 で引け、その前に下落 -0.52%
Innoviva Inc (INVA) last closed at $21.1200008, gaining +0.86%. These facts feed the 1-day and 1-week INVA price prediction above.
予想の要因
Innoviva Inc(INVA)の予想は、類似したチャートパターン・季節性・移動平均を組み合わせています。
Similar patterns
Bearish
Seasonality
Bullish
SMA 20
Bullish
SMA 200
Bearish
INVA の季節性分析
Historically the probability of a positive October return for INVA is 84.85%. August offers the highest probability of a positive month at 100.00%, while January is the weakest seasonal window. Alphio blends this calendar with technical signals and similar chart pattern matching before it writes the forecast.
INVA の10年価格予想
| 月 | 最低価格 | 平均価格 | 最高価格 | 想定 ROI |
|---|---|---|---|---|
| Oct 2026 | $16.32 | $21.35 | $22.83 | +1.11% |
| Nov 2026 | $21.99 | $26.37 | $30.60 | +24.85% |
| Dec 2026 | $16.70 | $19.37 | $20.18 | -8.31% |
2026年、Innoviva Inc(INVA)は $16.32 から $30.60 のレンジになると予想されます。
Innoviva Inc の 2026年 月次予想
2026年Oct、Innoviva Inc の平均は $21.35、安値 $16.32、高値 $22.83 と予想されます。
2026年Nov、Innoviva Inc の平均は $26.37、安値 $21.99、高値 $30.60 と予想されます。
2026年Dec、Innoviva Inc の平均は $19.37、安値 $16.70、高値 $20.18 と予想されます。
本ページは調査目的であり、投資助言ではありません。モデルは誤ることがあります。過去の実績は将来の成果を保証しません。