$2.810
-0.255 (-9.06%)Al cierre
Predicciones de precio
Ábrelo en la app para desbloquear previsiones a más largo plazo.
Predicción y previsión de BNC por análisis de gráficos similares
Alphio's BNC stock price prediction model matches the current CEA Industries Inc tape against historical breakout patterns, then publishes 1-day and 1-week targets first. The 1-day print is $2.81 (-0.17%). The 1-week path is $2.79 (-0.83%). 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 CEA Industries Inc?
BNC is a good buy right now due to its current price of $3.01, which is significantly lower than its 52-week high of $52.66, indicating a potential for recovery. The RSI is at 63.61, suggesting bullish momentum, and the gross margin has improved to 35.95% in the latest quarter, reflecting strong operational performance. However, the main risk is the high volatility indicated by an implied volatility of 199.25%, which could lead to sharp price movements.
BNC cerró en $2.81 el Tuesday, tras bajar -9.06%
CEA Industries Inc (BNC) last closed at $2.81, losing -9.06%. These facts feed the 1-day and 1-week BNC price prediction above.
Factores de la previsión
Los factores de la previsión de CEA Industries Inc (BNC) combinan patrones gráficos similares, estacionalidad y medias móviles.
Similar patterns
Bullish
Seasonality
Bearish
SMA 20
Bullish
SMA 200
Bearish
Patrones gráficos similares
Acciones cuya trayectoria reciente más se parece a la de BNC, ordenadas por similitud.
Análisis de estacionalidad de BNC
Historically the probability of a positive September return for BNC is 9.09%. August offers the highest probability of a positive month at 37.50%, while February is the weakest seasonal window. Alphio blends this calendar with technical signals and similar chart pattern matching before it writes the forecast.
Esta página es solo para investigación y no constituye asesoramiento de inversión. Los modelos pueden equivocarse. El rendimiento pasado no garantiza resultados futuros.