$12.730
+0.224 (+1.76%)Al cierre
Predicciones de precio
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Predicción y previsión de BBAR por análisis de gráficos similares
Alphio's BBAR stock price prediction model matches the current Banco BBVA Argentina SA tape against historical breakout patterns, then publishes 1-day and 1-week targets first. The 1-day print is $12.58 (-1.16%). The 1-week path is $12.33 (-3.18%). 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 Banco BBVA Argentina SA?
Banco BBVA Argentina is currently not a strong buy due to its recent performance and technical indicators. The current price is $12.78, with an RSI of 46.39 indicating a neutral momentum. Additionally, the forward P/E ratio stands at 3.22, suggesting it is undervalued, but the stock has a significant YTD change of -28.80%, indicating a downward trend. The main risk is the rising non-performing loan (NPL) ratio, which reached 6.09% in Q2 2026, highlighting potential asset quality issues.
BBAR cerró en $12.73 el Wednesday, tras subir +1.76%
Banco BBVA Argentina SA (BBAR) last closed at $12.73, gaining +1.76%. These facts feed the 1-day and 1-week BBAR price prediction above.
Factores de la previsión
Los factores de la previsión de Banco BBVA Argentina SA (BBAR) combinan patrones gráficos similares, estacionalidad y medias móviles.
Similar patterns
Bullish
Seasonality
Bearish
SMA 20
Bearish
SMA 200
Bearish
Patrones gráficos similares
Acciones cuya trayectoria reciente más se parece a la de BBAR, ordenadas por similitud.
Análisis de estacionalidad de BBAR
Historically the probability of a positive October return for BBAR is 37.10%. July offers the highest probability of a positive month at 66.67%, 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.