TransAlta Corp

TransAlta Corp(TAC)價格預測

$12.850

+0.193 (+1.50%)收盤時

價格預測

1-Day Price Prediction
-0.48%
1-Week Prediction
-1.11%
1-Month Prediction
—
2026 Prediction
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2030 Prediction
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在 App 中開啟以解鎖更長週期的預測。

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TAC 相似圖表分析預測

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 $12.79 (-0.48%). The 1-week path is $12.71 (-1.11%). 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.

該買進 TransAlta Corp 股票嗎?

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 股價於 Friday 收在 $12.85,此前上漲 +1.50%

TransAlta Corp (TAC) last closed at $12.85, gaining +1.50%. These facts feed the 1-day and 1-week TAC price prediction above.

分析師一致預期

TransAlta Corp(TAC):買進 0、持有 4、賣出 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

預測驅動因素

TransAlta Corp(TAC)的預測驅動因素綜合了相似的圖表形態、季節性與移動平均線。

Similar patterns

Positive

Bullish

Seasonality

Positive

Bullish

SMA 20

Positive

Bullish

SMA 200

Negative

Bearish

相似圖表形態

近期走勢與 TAC 最接近的股票,依相似度排序。

TAC 季節性分析

Historically the probability of a positive October return for TAC is 81.03%. 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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本頁僅供研究參考,不構成投資建議。模型可能出錯。過往表現不代表未來結果。

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