$12.190
-0.302 (-2.48%)At close
Price Predictions
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TAC Prediction & Forecast by Similar Chart Analysis
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 $12.08 (-0.94%). The 1-week path is $11.78 (-3.39%). 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.
Should I Buy TransAlta Corp Stock?
TransAlta Corp is currently not a strong buy due to mixed signals. The current price is C$12.19, with a forward P/E ratio of 79.37 indicating high valuation expectations. The RSI is at 39.87, suggesting the stock is nearing oversold territory, but the recent 20-day change is -2.48%, indicating a downward trend. The main risk is the high forward P/E ratio, which could lead to a significant price drop if earnings do not meet expectations.
TAC stock price ended at $12.19 on Friday, after losing -2.48%
TransAlta Corp (TAC) last closed at $12.19, losing -2.48%. These facts feed the 1-day and 1-week TAC price prediction above.
Analyst Consensus
TransAlta Corp (TAC): 0 buy, 4 hold, 0 sell. Outlook: Hold.
Sell / Buy
Technical signals summary based on buy and sell indicators. The gauge shows the overall market view.
Forecast Drivers
TransAlta Corp (TAC) forecast drivers combine similar chart patterns, seasonality, and moving averages.
Similar patterns
Bullish
Seasonality
Bearish
SMA 20
Bearish
SMA 200
Bearish
Similar Chart Patterns
Stocks whose recent price path most closely matches TAC, ranked by similarity.
Seasonality analysis for TAC
Historically the probability of a positive August return for TAC is 23.81%. October offers the highest probability of a positive month at 95.65%, while March is the weakest seasonal window. Alphio blends this calendar with technical signals and similar chart pattern matching before it writes the forecast.
This page is for research only and is not investment advice. Models can be wrong. Past performance does not guarantee future results.