$1.280
+0.132 (+10.34%)Al cierre
Predicciones de precio
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Predicción y previsión de TRNR por análisis de gráficos similares
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 $1.27 (-0.48%). The 1-week path is $1.28 (+0.34%). 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.
¿Debería comprar acciones de Interactive Strength Inc?
TRNR is not a good buy right now. The current price is $1.16, which is significantly down 98.16% year-to-date, indicating severe market distress. The RSI is at 17.25, suggesting the stock is heavily oversold, but this alone does not guarantee a rebound. The gross margin has improved to 48.37% in Q2 2026, but the company still reported a net income loss of $7.1 million in the same quarter, highlighting ongoing financial struggles. The main risk is the high debt-to-equity ratio of 638.76%, which poses a significant financial burden and risk to investors.
TRNR cerró en $1.28 el Monday, tras subir +10.34%
Interactive Strength Inc (TRNR) last closed at $1.28, gaining +10.34%. These facts feed the 1-day and 1-week TRNR price prediction above.
Factores de la previsión
Los factores de la previsión de Interactive Strength Inc (TRNR) combinan patrones gráficos similares, estacionalidad y medias móviles.
Similar patterns
Bullish
Seasonality
Bearish
SMA 20
Bearish
SMA 200
Bearish
Patrones gráficos similares
Acciones cuya trayectoria reciente más se parece a la de TRNR, ordenadas por similitud.
Análisis de estacionalidad de TRNR
Historically the probability of a positive November 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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Esta página es solo para investigación y no constituye asesoramiento de inversión. Los modelos pueden equivocarse. El rendimiento pasado no garantiza resultados futuros.