SUMA Acquisition Corp

Predicción y previsión de precio de SUMA Acquisition Corp (SUMA)

$9.990

0.000 (0.00%)Al cierre

Predicciones de precio

1-Day Price Prediction
-1.05%
1-Week Prediction
-0.23%
1-Month Prediction
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2026 Prediction
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2030 Prediction
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Ábrelo en la app para desbloquear previsiones a más largo plazo.

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Predicción y previsión de SUMA por análisis de gráficos similares

Alphio's SUMA stock price prediction model matches the current SUMA Acquisition Corp tape against historical breakout patterns, then publishes 1-day and 1-week targets first. The 1-day print is $9.89 (-1.05%). The 1-week path is $9.97 (-0.23%). 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 SUMA Acquisition Corp?

Suma Acquisition Corp is currently trading at $9.99, which is 86.5% of its 52-week range. The RSI is at 83.158, indicating that the stock is overbought. Although the company has shown a positive net income growth from $152,021 in Q1 to $1,328,840 in Q2, the high P/E ratio of 157.70 suggests that the stock may be overvalued at this price. The main risk is the lack of significant trading trends, as indicated by neutral insider and hedge fund activities, which may lead to price stagnation.

SUMA cerró en $9.99 el Wednesday, tras subir 0.00%

SUMA Acquisition Corp (SUMA) last closed at $9.9899998, gaining +0.00%. These facts feed the 1-day and 1-week SUMA price prediction above.

Factores de la previsión

Los factores de la previsión de SUMA Acquisition Corp (SUMA) combinan patrones gráficos similares, estacionalidad y medias móviles.

Similar patterns

Positive

Bullish

Seasonality

Positive

Bullish

SMA 20

Positive

Bullish

SMA 200

Positive

Bullish

Patrones gráficos similares

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

Análisis de estacionalidad de SUMA

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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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