$19.660
-0.090 (-0.46%)Al cierre
Predicciones de precio
Ábrelo en la app para desbloquear previsiones a más largo plazo.
Predicción y previsión de SI por análisis de gráficos similares
Alphio's SI stock price prediction model matches the current Shoulder Innovations Inc tape against historical breakout patterns, then publishes 1-day and 1-week targets first. The 1-day print is $19.59 (-0.37%). The 1-week path is $20.60 (+4.80%). 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 Shoulder Innovations Inc?
Shoulder Innovations Inc is a good buy right now, trading at $19.66 with a strong RSI of 73.32, indicating bullish momentum. The company recently reported a significant revenue increase to $17.2 million in Q2 2026, surpassing expectations, and has a gross margin of 78.3%, showcasing effective cost management. However, the main risk is the negative earnings per share of -0.49 expected in the next quarter, which could impact investor sentiment.
SI cerró en $19.66 el Friday, tras bajar -0.46%
Shoulder Innovations Inc (SI) last closed at $19.66, losing -0.46%. These facts feed the 1-day and 1-week SI price prediction above.
Factores de la previsión
Los factores de la previsión de Shoulder Innovations Inc (SI) combinan patrones gráficos similares, estacionalidad y medias móviles.
Similar patterns
Bullish
Seasonality
Bearish
SMA 20
Bullish
SMA 200
Bullish
Patrones gráficos similares
Acciones cuya trayectoria reciente más se parece a la de SI, ordenadas por similitud.
Análisis de estacionalidad de SI
Historically the probability of a positive October return for SI is 42.50%. July offers the highest probability of a positive month at 95.83%, 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.