$2.020
+0.073 (+3.59%)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 SLDP の予測・予想
Alphio's SLDP stock price prediction model matches the current Solid Power Inc tape against historical breakout patterns, then publishes 1-day and 1-week targets first. The 1-day print is $2.07 (-0.25%). The 1-week path is $2.05 (-1.60%). 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.
Solid Power Inc 株は買うべき?
Solid Power Inc (SLDP) is not a good buy right now due to its poor financial performance and negative price momentum. The current price is $2.01, and the stock has seen a year-to-date change of -56.77%, indicating significant losses. Additionally, the RSI is at 22.035, suggesting that the stock is oversold but may continue to face downward pressure.
SLDP の株価は Tuesday に $2.02 で引け、その前に上昇 +3.59%
Solid Power Inc (SLDP) last closed at $2.08, gaining +2.97%. These facts feed the 1-day and 1-week SLDP price prediction above.
予想の要因
Solid Power Inc(SLDP)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
Bullish
Seasonality
Bearish
SMA 20
Bearish
SMA 200
Bearish
類似チャートパターン
直近の値動きが SLDP に最も近い銘柄を、類似度順に表示します。
SLDP の季節性分析
Historically the probability of a positive October return for SLDP is 37.70%. July offers the highest probability of a positive month at 66.67%, while March is the weakest seasonal window. Alphio blends this calendar with technical signals and similar chart pattern matching before it writes the forecast.
SLDP 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 | $1.96 | $2.24 | $2.68 | +7.67% |
| Nov 2026 | $2.00 | $2.19 | $2.41 | +5.17% |
| Dec 2026 | $2.18 | $2.34 | $2.60 | +12.49% |
2026年、Solid Power Inc(SLDP)は $1.96 から $2.68 のレンジになると予想されます。
Solid Power Inc の 2026年 月次予想
2026年Oct、Solid Power Inc の平均は $2.24、安値 $1.96、高値 $2.68 と予想されます。
2026年Nov、Solid Power Inc の平均は $2.19、安値 $2.00、高値 $2.41 と予想されます。
2026年Dec、Solid Power Inc の平均は $2.34、安値 $2.18、高値 $2.60 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。