Interactive Strength Inc

Interactive Strength Inc(TRNR)の株価予測

$3.030

+0.152 (+5.03%)終値時点

価格予想

1-Day Price Prediction
+0.34%
1-Week Prediction
+4.88%
1-Month Prediction
2026 Prediction
2030 Prediction

アプリで開くと、より長期の予想を確認できます。

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類似チャート分析による TRNR の予測・予想

Alphio's TRNR stock price prediction model matches the current Interactive Strength Inc tape against historical breakout patterns, then publishes 1-day and 1-week targets first. The 1-day print is $2.91 (+0.34%). The 1-week path is $3.04 (+4.88%). 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.

Interactive Strength Inc 株は買うべき?

Currently, Interactive Strength Inc (TRNR) is not a strong buy due to its substantial year-to-date decline of 95.24% and a low RSI of 36.253, indicating potential oversold conditions but also a lack of upward momentum. The recent acquisition of STEPR and the raised revenue guidance to over $50 million for 2026 are positive signs, but the company continues to face significant financial challenges, including a net income loss of $7,104,000 in Q2 2026. The main risk is the high debt-to-equity ratio of 924.13%, which raises concerns about financial stability.

TRNR の株価は Wednesday に $3.03 で引け、その前に上昇 +5.03%

Interactive Strength Inc (TRNR) last closed at $2.898, losing -4.36%. These facts feed the 1-day and 1-week TRNR price prediction above.

予想の要因

Interactive Strength Inc(TRNR)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

Positive

Bullish

Seasonality

Negative

Bearish

SMA 20

Negative

Bearish

SMA 200

Negative

Bearish

類似チャートパターン

直近の値動きが TRNR に最も近い銘柄を、類似度順に表示します。

TRNR の季節性分析

Historically the probability of a positive September return for TRNR is 0.00%. January offers the highest probability of a positive month at 21.31%, while February is the weakest seasonal window. Alphio blends this calendar with technical signals and similar chart pattern matching before it writes the forecast.

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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。

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