TransAlta Corp

TransAlta Corp(TAC)价格预测

$13.340

+0.380 (+2.85%)收盘时

价格预测

1-Day Price Prediction
-0.13%
1-Week Prediction
+1.39%
1-Month Prediction
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2026 Prediction
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2030 Prediction
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在 App 中打开以解锁更长周期的预测。

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TAC 相似图表分析预测

Alphio's TAC stock price prediction model matches the current TransAlta Corp tape against historical breakout patterns, then publishes 1-day and 1-week targets first. The 1-day print is $12.49 (-0.13%). The 1-week path is $12.68 (+1.39%). 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.

该买入 TransAlta Corp 股票吗?

TransAlta Corp is a good buy right now due to its recent positive financial performance, including a Q2 adjusted EPS of C$0.18, which exceeded estimates by C$0.16, and a gross margin of 58.38% in Q2 2026. The acquisition of natural gas facilities is expected to enhance revenue by approximately C$80 million annually, providing a strong growth catalyst. However, the company has a high debt-to-equity ratio of 229.26%, which poses a risk to its financial stability.

TAC 股价于 Wednesday 收于 $13.34,此前上涨 +2.85%

TransAlta Corp (TAC) last closed at $12.51, losing -6.22%. These facts feed the 1-day and 1-week TAC price prediction above.

分析师一致预期

TransAlta Corp(TAC):买入 0、持有 4、卖出 0。展望:Hold。

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

Strong sellSellNeutralBuyStrong buy
Neutral
Sell
0
Buy
0

预测驱动因素

TransAlta Corp(TAC)的预测驱动因素综合了相似的图表形态、季节性与移动平均线。

Similar patterns

Positive

Bullish

Seasonality

Positive

Bullish

SMA 20

Negative

Bearish

SMA 200

Negative

Bearish

相似图表形态

近期走势与 TAC 最接近的股票,按相似度排序。

TAC 季节性分析

Historically the probability of a positive October return for TAC is 77.42%. November offers the highest probability of a positive month at 89.74%, while March 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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本页仅供研究参考,不构成投资建议。模型可能出错。过往表现不代表未来结果。

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