Canadian National Railway Co

Predicción y previsión de precio de Canadian National Railway Co (CNI)

$126.010

-0.466 (-0.37%)Al cierre

Predicciones de precio

1-Day Price Prediction
-1.42%
1-Week Prediction
+1.74%
1-Month Prediction
2026 Prediction
2030 Prediction

Ábrelo en la app para desbloquear previsiones a más largo plazo.

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Predicción y previsión de CNI por análisis de gráficos similares

Alphio's CNI stock price prediction model matches the current Canadian National Railway Co tape against historical breakout patterns, then publishes 1-day and 1-week targets first. The 1-day print is $124.22 (-1.42%). The 1-week path is $128.20 (+1.74%). 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 Canadian National Railway Co?

Canadian National Railway Co is currently a hold. The stock is priced at $126.01, which is about 13.7% overvalued based on cash flow estimates. The RSI of 37.154 indicates that the stock is in a bearish trend, suggesting potential further downside. However, the company has shown strong financial performance with a 30.40% increase over the past year and a gross margin of 62.42%. The main risk is its current valuation, which is higher than intrinsic value estimates, indicating that new investors may face challenges in achieving immediate gains.

CNI cerró en $126.01 el Friday, tras bajar -0.37%

Canadian National Railway Co (CNI) last closed at $126.01, losing -0.37%. These facts feed the 1-day and 1-week CNI price prediction above.

Consenso de analistas

Canadian National Railway Co (CNI): 9 comprar, 16 mantener, 1 vender. Perspectiva: Hold.

Technical signals summary based on buy and sell indicators. The gauge shows the overall market view.

Strong sellSellNeutralBuyStrong buy
Strong buy
Sell
1
Buy
9

Factores de la previsión

Los factores de la previsión de Canadian National Railway Co (CNI) combinan patrones gráficos similares, estacionalidad y medias móviles.

Similar patterns

Positive

Bullish

Seasonality

Negative

Bearish

SMA 20

Negative

Bearish

SMA 200

Positive

Bullish

Patrones gráficos similares

Acciones cuya trayectoria reciente más se parece a la de CNI, ordenadas por similitud.

Análisis de estacionalidad de CNI

Historically the probability of a positive August return for CNI is 31.75%. February offers the highest probability of a positive month at 77.59%, while September 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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Proyecciones de precio a 10 años de CNI

MesPrecio mínimoPrecio medioPrecio máximoROI potencial
Aug 2026$115.54$123.70$124.77-1.84%
Sep 2026$77.88$91.14$111.19-27.67%
Oct 2026$88.25$107.19$124.32-14.94%
Nov 2026$104.49$108.79$124.50-13.67%
Dec 2026$82.79$91.14$95.83-27.67%

En 2026, se proyecta que Canadian National Railway Co (CNI) oscile entre $77.88 y $124.77.

Previsión mensual de Canadian National Railway Co para 2026

Previsión de CNI para Aug de 2026
ROI potencial: -1.84%

En Aug de 2026, se proyecta que Canadian National Railway Co promedie $123.70, con un mínimo de $115.54 y un máximo de $124.77.

Previsión de CNI para Sep de 2026
ROI potencial: -27.67%

En Sep de 2026, se proyecta que Canadian National Railway Co promedie $91.14, con un mínimo de $77.88 y un máximo de $111.19.

Previsión de CNI para Oct de 2026
ROI potencial: -14.94%

En Oct de 2026, se proyecta que Canadian National Railway Co promedie $107.19, con un mínimo de $88.25 y un máximo de $124.32.

Previsión de CNI para Nov de 2026
ROI potencial: -13.67%

En Nov de 2026, se proyecta que Canadian National Railway Co promedie $108.79, con un mínimo de $104.49 y un máximo de $124.50.

Previsión de CNI para Dec de 2026
ROI potencial: -27.67%

En Dec de 2026, se proyecta que Canadian National Railway Co promedie $91.14, con un mínimo de $82.79 y un máximo de $95.83.

Esta página es solo para investigación y no constituye asesoramiento de inversión. Los modelos pueden equivocarse. El rendimiento pasado no garantiza resultados futuros.

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