$9.430
-0.070 (-0.74%)Al cierre
Predicciones de precio
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Predicción y previsión de BRSL por análisis de gráficos similares
Alphio's BRSL stock price prediction model matches the current Brightstar Lottery PLC tape against historical breakout patterns, then publishes 1-day and 1-week targets first. The 1-day print is $9.27 (-0.92%). The 1-week path is $9.12 (-2.53%). 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 Brightstar Lottery PLC?
Brightstar Lottery PLC appears to be a good buy right now due to its recent positive earnings surprise and analyst upgrades. The stock has a current price of $9.5, with analysts projecting a price target of $16, representing a potential upside of 68%. Additionally, the company's recent signing of an exclusive agreement with Pan American World Airways for lottery games could drive future revenue growth. However, the stock has seen a year-to-date decline of 37.91%, indicating some volatility and risk.
BRSL cerró en $9.43 el Monday, tras bajar -0.74%
Brightstar Lottery PLC (BRSL) last closed at $9.36, losing -0.74%. These facts feed the 1-day and 1-week BRSL price prediction above.
Factores de la previsión
Los factores de la previsión de Brightstar Lottery PLC (BRSL) combinan patrones gráficos similares, estacionalidad y medias móviles.
Similar patterns
Bullish
Seasonality
Bullish
SMA 20
Bearish
SMA 200
Bearish
Patrones gráficos similares
Acciones cuya trayectoria reciente más se parece a la de BRSL, ordenadas por similitud.
Análisis de estacionalidad de BRSL
Historically the probability of a positive October return for BRSL is 62.16%. October offers the highest probability of a positive month at 62.16%, 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.