$3.685
+0.025 (+0.68%)Al cierre
Predicciones de precio
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Predicción y previsión de IVA por análisis de gráficos similares
Alphio's IVA stock price prediction model matches the current Inventiva SA tape against historical breakout patterns, then publishes 1-day and 1-week targets first. The 1-day print is $3.64 (-1.10%). The 1-week path is $3.58 (-2.79%). 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 Inventiva SA?
Inventiva SA (IVA) is a good buy right now due to its recent price increase of 26.19% over the last 5 days and a strong cash position of €166.1 million, which supports its operations and R&D. Furthermore, analysts have set price targets significantly higher than the current price of $3.71, with the highest target at $21, indicating a potential upside of over 465%. The main risk is the company's negative P/E ratio of -1.42, reflecting ongoing losses, but the narrowing of losses and improved cash flow management suggest a path toward profitability.
IVA cerró en $3.68 el Tuesday, tras subir +0.68%
Inventiva SA (IVA) last closed at $3.6849999, gaining +0.68%. These facts feed the 1-day and 1-week IVA price prediction above.
Factores de la previsión
Los factores de la previsión de Inventiva SA (IVA) 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 IVA, ordenadas por similitud.
Análisis de estacionalidad de IVA
Historically the probability of a positive October return for IVA is 35.38%. March offers the highest probability of a positive month at 68.25%, while July 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.