$21.930
+0.564 (+2.57%)Al cierre
Predicciones de precio
Ábrelo en la app para desbloquear previsiones a más largo plazo.
Predicción y previsión de NRC por análisis de gráficos similares
Alphio's NRC stock price prediction model matches the current National Research Corp tape against historical breakout patterns, then publishes 1-day and 1-week targets first. The 1-day print is $21.99 (+0.29%). The 1-week path is $21.24 (-3.14%). 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 National Research Corp?
National Research Corp (NRC) is a good buy right now due to its strong recent performance, with a current price of $21.93 and a year-to-date change of +21.63%. The company has shown resilience with a gross margin of 56.41% and a forward P/E ratio of 17.21, indicating potential for future earnings growth. However, the main risk is its high debt-to-equity ratio of 1374.68%, which could impact financial stability if not managed properly.
NRC cerró en $21.93 el Friday, tras subir +2.57%
National Research Corp (NRC) last closed at $21.93, gaining +2.57%. These facts feed the 1-day and 1-week NRC price prediction above.
Factores de la previsión
Los factores de la previsión de National Research Corp (NRC) 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 NRC, ordenadas por similitud.
Análisis de estacionalidad de NRC
Historically the probability of a positive October return for NRC is 26.98%. January offers the highest probability of a positive month at 47.54%, while March 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.