HDRN

Predicción y previsión de precio de HDRN (HDRN)

$0.681

+0.006 (+0.90%)Al cierre

Predicciones de precio

1-Day Price Prediction
-0.34%
1-Week Prediction
-5.57%
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 HDRN por análisis de gráficos similares

Alphio's HDRN stock price prediction model matches the current HDRN tape against historical breakout patterns, then publishes 1-day and 1-week targets first. The 1-day print is $0.68 (-0.34%). The 1-week path is $0.64 (-5.57%). 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 HDRN?

Hadron Energy, Inc. is not a good buy right now due to its significant decline in price and poor financial performance. The current price is 0.66, which is 87.20% lower than its year-to-date performance. Additionally, the RSI is at 31.51, indicating it is oversold, but this does not guarantee a recovery. The forward P/E is 0, reflecting a lack of earnings expectations, and the gross margin is negative at -0.01%, suggesting ongoing financial difficulties. The main risk is the upcoming earnings report on November 13, 2026, where the EPS estimate is -0.09, indicating continued losses.

HDRN cerró en $0.68 el Friday, tras subir +0.90%

HDRN (HDRN) last closed at $0.6811, gaining +0.90%. These facts feed the 1-day and 1-week HDRN price prediction above.

Factores de la previsión

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

Similar patterns

Positive

Bullish

Seasonality

Negative

Bearish

SMA 20

Negative

Bearish

SMA 200

Negative

Bearish

Patrones gráficos similares

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

Análisis de estacionalidad de HDRN

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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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