$2.800
+0.030 (+1.08%)Al cierre
Predicciones de precio
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Predicción y previsión de GNLN por análisis de gráficos similares
Alphio's GNLN stock price prediction model matches the current Greenlane Holdings Inc tape against historical breakout patterns, then publishes 1-day and 1-week targets first. The 1-day print is $2.82 (+0.69%). The 1-week path is $2.84 (+1.49%). 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 Greenlane Holdings Inc?
Greenlane Holdings Inc is not a good buy right now due to significant financial losses and declining revenue. The company reported a GAAP EPS of -11.42 for FY 2023 and a revenue decline of 66.9% year-over-year, indicating severe challenges in profitability and market demand. Furthermore, the forward P/E ratio stands at 192.31, suggesting that the stock is overvalued relative to its earnings potential. The main risk is its recent performance, with a YTD change of -77.85%, indicating a lack of investor confidence and potential liquidity issues.
GNLN cerró en $2.80 el Friday, tras subir +1.08%
Greenlane Holdings Inc (GNLN) last closed at $2.8, gaining +1.08%. These facts feed the 1-day and 1-week GNLN price prediction above.
Factores de la previsión
Los factores de la previsión de Greenlane Holdings Inc (GNLN) 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 GNLN, ordenadas por similitud.
Análisis de estacionalidad de GNLN
Historically the probability of a positive August return for GNLN is 20.31%. May offers the highest probability of a positive month at 34.92%, 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.