Santacruz Silver Mining Ltd

Predicción y previsión de precio de Santacruz Silver Mining Ltd (SCZM)

$9.200

-0.157 (-1.71%)Al cierre

Predicciones de precio

1-Day Price Prediction
-1.65%
1-Week Prediction
-2.15%
1-Month Prediction
2026 Prediction
2030 Prediction

Ábrelo en la app para desbloquear previsiones a más largo plazo.

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Predicción y previsión de SCZM por análisis de gráficos similares

Alphio's SCZM stock price prediction model matches the current Santacruz Silver Mining Ltd tape against historical breakout patterns, then publishes 1-day and 1-week targets first. The 1-day print is $9.05 (-1.65%). The 1-week path is $9.00 (-2.15%). 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 Santacruz Silver Mining Ltd?

Santacruz Silver Mining Ltd is a good buy right now due to its recent strong revenue growth and favorable market conditions. The latest earnings report showed a significant revenue increase of 81.4% year-over-year, reaching $127.53 million in Q1 2026. Additionally, the RSI is at 54.61, indicating a neutral momentum, while the stock is currently trading at $9.52, which is below the analyst's revised price target of $10, suggesting a potential upside of about 5%.

SCZM cerró en $9.20 el Tuesday, tras bajar -1.71%

Santacruz Silver Mining Ltd (SCZM) last closed at $9.2, losing -1.71%. These facts feed the 1-day and 1-week SCZM price prediction above.

Factores de la previsión

Los factores de la previsión de Santacruz Silver Mining Ltd (SCZM) combinan patrones gráficos similares, estacionalidad y medias móviles.

Similar patterns

Positive

Bullish

Seasonality

Negative

Bearish

SMA 20

Positive

Bullish

SMA 200

Positive

Bullish

Patrones gráficos similares

Acciones cuya trayectoria reciente más se parece a la de SCZM, ordenadas por similitud.

Análisis de estacionalidad de SCZM

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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.

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