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Foremost Clean Energy Stock Price Chart

  • Based on the share price being above its 5, 20 & 50 day exponential moving averages, the current trend is considered strongly bullish and FMST is experiencing slight buying pressure.

Foremost Clean Energy Price Chart Indicators

Moving Averages Level Buy or Sell
8-day SMA: 3.29 Sell
20-day SMA: 3.46 Sell
50-day SMA: 2.77 Buy
200-day SMA: 1.88 Buy
8-day EMA: 0.71 Buy
20-day EMA: 0.3 Buy
50-day EMA: 0.13 Buy
200-day EMA: 0.03 Buy

Foremost Clean Energy Technical Analysis Indicators

Chart Indicators Level Buy or Sell
MACD (12, 26): 0.25 Buy
Relative Strength Index (14 RSI): 48.54 Sell
Chaikin Money Flow: 57996 -
Bollinger Bands Level Buy or Sell
Bollinger Bands (25): (3.12 - 4.32) Sell
Bollinger Bands (100): (0.47 - 3.11) Buy

Foremost Clean Energy 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 Foremost Clean Energy Stock

Is Foremost Clean Energy Stock a Buy?

FMST Technical Analysis vs Fundamental Analysis

Sell
41
Foremost Clean Energy (FMST) is a Sell

Is Foremost Clean Energy a Buy or a Sell?

Foremost Clean Energy Stock Info

Market Cap:
38.1M
Price in USD:
3.19
Share Volume:
174K

Foremost Clean Energy 52-Week Range

52-Week High:
5.74
52-Week Low:
0.55
Sell
41
Foremost Clean Energy (FMST) is a Sell

Foremost Clean Energy Share Price Forecast

Is Foremost Clean Energy Stock a Buy?

Fundamental Analysis of Foremost Clean Energy

Is Foremost Clean Energy a good investment?

  • Analysts estimate an earnings increase this quarter of $0.00 per share, a decrease next quarter of $0.00 per share, an increase this year of $0.15 per share, and a decrease next year of $0.00 per share.

Technical Analysis of Foremost Clean Energy

Should I short Foremost Clean Energy stock?

* Foremost Clean Energy stock forecasts short-term for next days and weeks may differ from long term prediction for next month and year based on timeline differences.