$25.360
-0.355 (-1.40%)Al cierre
Predicciones de precio
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Predicción y previsión de FIGR por análisis de gráficos similares
Alphio's FIGR stock price prediction model matches the current Figure Technology Solutions Inc tape against historical breakout patterns, then publishes 1-day and 1-week targets first. The 1-day print is $26.05 (+8.35%). The 1-week path is $25.46 (+5.91%). 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 Figure Technology Solutions Inc?
Currently, FIGR is not a strong buy. The stock is priced at $27.13, with an RSI of 42.99 indicating it is near oversold territory. However, the forward P/E ratio is 0, which suggests uncertainty in future earnings. The stock has seen a significant decline of 37.97% year-to-date, and while there are positive earnings surprises, the recent insider selling raises concerns. Therefore, it may be wise to hold off on buying until clearer upward momentum is established.
FIGR cerró en $25.36 el Wednesday, tras bajar -1.40%
Figure Technology Solutions Inc (FIGR) last closed at $24.04, losing -5.21%. These facts feed the 1-day and 1-week FIGR price prediction above.
Factores de la previsión
Los factores de la previsión de Figure Technology Solutions Inc (FIGR) 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 FIGR, ordenadas por similitud.
Análisis de estacionalidad de FIGR
Historically the probability of a positive October return for FIGR is 58.97%. November offers the highest probability of a positive month at 100.00%, 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.