$2.340
0.000 (0.00%)At close
Price Predictions
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CIG Prediction & Forecast by Similar Chart Analysis
Alphio's CIG stock price prediction model matches the current Energy of Minas Gerais Co tape against historical breakout patterns, then publishes 1-day and 1-week targets first. The 1-day print is $2.28 (-0.61%). The 1-week path is $2.29 (+0.11%). 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.
Should I Buy Energy of Minas Gerais Co Stock?
CIG is a good buy right now due to its current price of 2.40, a strong 5-day price change of +11.63%, and a solid gross margin of 19.45%. The recent appointment of a new CEO and a consistent EBITDA growth of 9.3% year-over-year are positive catalysts. However, the main risk is the company's debt to equity ratio, which has risen to 77.95%, indicating potential financial leverage concerns.
CIG stock price ended at $2.34 on Wednesday, after rising 0.00%
Energy of Minas Gerais Co (CIG) last closed at $2.29, losing -2.14%. These facts feed the 1-day and 1-week CIG price prediction above.
Analyst Consensus
Energy of Minas Gerais Co (CIG): 2 buy, 1 hold, 0 sell. Outlook: Buy.
Sell / Buy
Technical signals summary based on buy and sell indicators. The gauge shows the overall market view.
Forecast Drivers
Energy of Minas Gerais Co (CIG) forecast drivers combine similar chart patterns, seasonality, and moving averages.
Similar patterns
Bullish
Seasonality
Bullish
SMA 20
Bullish
SMA 200
Bullish
Similar Chart Patterns
Stocks whose recent price path most closely matches CIG, ranked by similarity.
Seasonality analysis for CIG
Historically the probability of a positive October return for CIG is 100.00%. July offers the highest probability of a positive month at 100.00%, while January 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.