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Gentera SAB de CV Stock Price Chart

  • The current trend is relatively stagnant and CMPRF is experiencing slight buying pressure.

Gentera SAB de CV Price Chart Indicators

Moving Averages Level Buy or Sell
8-day SMA: 2.33 Sell
20-day SMA: 2.32 Buy
50-day SMA: 2.49 Sell
200-day SMA: 2.05 Buy
8-day EMA: 2.33 Buy
20-day EMA: 2.35 Sell
50-day EMA: 2.39 Sell
200-day EMA: 1.64 Buy

Gentera SAB de CV Technical Analysis Indicators

Chart Indicators Level Buy or Sell
MACD (12, 26): -0.04 Sell
Relative Strength Index (14 RSI): 23.62 Sell
Chaikin Money Flow: 0 -
Bollinger Bands Level Buy or Sell
Bollinger Bands (25): (2.3 - 2.32) Buy
Bollinger Bands (100): (2.1 - 2.66) Sell

Gentera SAB de CV Technical Analysis

Technical Analysis: Buy or Sell?
8-day SMA:
20-day SMA:
50-day SMA:
200-day SMA:
8-day EMA:
20-day EMA:
50-day EMA:
200-day EMA:
MACD (12, 26):
Relative Strength Index (14 RSI):
Bollinger Bands (25):
Bollinger Bands (100):

Technical Analysis for Gentera SAB de CV Stock

Is Gentera SAB de CV Stock a Buy?

CMPRF Technical Analysis vs Fundamental Analysis

Buy
55
Gentera SAB de CV (CMPRF) is a Buy

Is Gentera SAB de CV a Buy or a Sell?

Gentera SAB de CV Stock Info

Market Cap:
3.7B
Price in USD:
2.33
Share Volume:
0

Gentera SAB de CV 52-Week Range

52-Week High:
2.67
52-Week Low:
1.36
Buy
55
Gentera SAB de CV (CMPRF) is a Buy

Gentera SAB de CV Share Price Forecast

Is Gentera SAB de CV Stock a Buy?

  • Gentera SAB de CV share price is 2.33 while CMPRF 8-day exponential moving average is 2.33, which is a Buy signal.
  • The stock price of CMPRF is 2.33 while Gentera SAB de CV 20-day EMA is 2.35, which makes it a Sell.
  • Gentera SAB de CV 50-day exponential moving average is 2.39 while CMPRF share price is 2.33, making it a Sell technically.
  • CMPRF stock price is 2.33 and Gentera SAB de CV 200-day simple moving average is 1.64, creating a Buy signal.

Technical Analysis of Gentera SAB de CV

Should I short Gentera SAB de CV stock?

* Gentera SAB de CV stock forecasts short-term for next days and weeks may differ from long term prediction for next month and year based on timeline differences.