$4.490
-0.164 (-3.65%)Al cierre
Predicciones de precio
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Predicción y previsión de SOC por análisis de gráficos similares
Alphio's SOC stock price prediction model matches the current Sable Offshore Corp tape against historical breakout patterns, then publishes 1-day and 1-week targets first. The 1-day print is $4.49 (+0.07%). The 1-week path is $4.59 (+2.19%). 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 Sable Offshore Corp?
Sable Offshore Corp is not a good buy right now due to its current price of $4.49, which is significantly below the analyst price targets of $9 and $11. The stock has seen a year-to-date change of -61.72% and a one-year change of -80.55%, indicating substantial declines. However, a recent court ruling allowing continued pipeline operations has generated some optimism, leading to a 28% surge in stock price. The main risk is the negative earnings performance, as the last earnings report showed an EPS surprise of -76.19%.
SOC cerró en $4.49 el Friday, tras bajar -3.65%
Sable Offshore Corp (SOC) last closed at $4.49, losing -3.65%. These facts feed the 1-day and 1-week SOC price prediction above.
Factores de la previsión
Los factores de la previsión de Sable Offshore Corp (SOC) combinan patrones gráficos similares, estacionalidad y medias móviles.
Similar patterns
Bullish
Seasonality
Bullish
SMA 20
Bearish
SMA 200
Bearish
Patrones gráficos similares
Acciones cuya trayectoria reciente más se parece a la de SOC, ordenadas por similitud.
Análisis de estacionalidad de SOC
Historically the probability of a positive August return for SOC is 68.25%. March offers the highest probability of a positive month at 73.02%, while April 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.