$0.980
+0.036 (+3.70%)Al cierre
Predicciones de precio
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Predicción y previsión de POM por análisis de gráficos similares
Alphio's POM stock price prediction model matches the current PomDoctor Ltd tape against historical breakout patterns, then publishes 1-day and 1-week targets first. The 1-day print is $0.98 (+0.11%). The 1-week path is $1.00 (+1.55%). 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 PomDoctor Ltd?
Currently, PomDoctor Ltd is not a strong buy. The stock price is at 0.95, which is significantly down 83.80% year-to-date and 98.68% over the past year. The RSI is at 50.15, indicating a neutral momentum, and the forward P/E is at 0, suggesting a lack of earnings expectations. While there was a positive revenue growth of 16.7% reported for FY 2025, the gross margin has declined to 13.1%, indicating profitability pressures. The main risk is the company's negative equity of -2.26 billion CNY, which raises concerns about financial stability.
POM cerró en $0.98 el Tuesday, tras subir +3.70%
PomDoctor Ltd (POM) last closed at $0.98, gaining +3.70%. These facts feed the 1-day and 1-week POM price prediction above.
Factores de la previsión
Los factores de la previsión de PomDoctor Ltd (POM) combinan patrones gráficos similares, estacionalidad y medias móviles.
Similar patterns
Bullish
Seasonality
Bearish
SMA 20
Bullish
SMA 200
Bearish
Patrones gráficos similares
Acciones cuya trayectoria reciente más se parece a la de POM, ordenadas por similitud.
Análisis de estacionalidad de POM
Historically the probability of a positive September return for POM is 0.00%. October offers the highest probability of a positive month at 94.74%, 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.