$106.050
-1.548 (-1.46%)Al cierre
Predicciones de precio
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Predicción y previsión de LLYVK por análisis de gráficos similares
Alphio's LLYVK stock price prediction model matches the current Liberty Media Corp tape against historical breakout patterns, then publishes 1-day and 1-week targets first. The 1-day print is $106.21 (+0.15%). The 1-week path is $111.97 (+5.58%). 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.
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Liberty Live Holdings, Inc. Series C is currently trading at $106.05, which is close to its 52-week high of $112.99, indicating limited upside potential. The RSI is at 48.61, suggesting the stock is neither overbought nor oversold, which aligns with a neutral market sentiment. While the stock has shown a strong year-to-date change of +26.01%, the forward P/E ratio is quite high at 49.75, indicating potential overvaluation. The main risk is the high forward P/E, which could lead to a price correction if earnings do not meet expectations.
LLYVK cerró en $106.05 el Friday, tras bajar -1.46%
Liberty Media Corp (LLYVK) last closed at $106.0500031, losing -1.46%. These facts feed the 1-day and 1-week LLYVK price prediction above.
Factores de la previsión
Los factores de la previsión de Liberty Media Corp (LLYVK) combinan patrones gráficos similares, estacionalidad y medias móviles.
Similar patterns
Bullish
Seasonality
Bullish
SMA 20
Bullish
SMA 200
Bullish
Patrones gráficos similares
Acciones cuya trayectoria reciente más se parece a la de LLYVK, ordenadas por similitud.
Análisis de estacionalidad de LLYVK
Historically the probability of a positive November return for LLYVK is 100.00%. May offers the highest probability of a positive month at 100.00%, while January is the weakest seasonal window. Alphio blends this calendar with technical signals and similar chart pattern matching before it writes the forecast.
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Esta página es solo para investigación y no constituye asesoramiento de inversión. Los modelos pueden equivocarse. El rendimiento pasado no garantiza resultados futuros.