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First Trust Global Wind Energy ETF 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 FAN is experiencing buying pressure, which is a positive indicator for future bullish movement.

First Trust Global Wind Energy ETF Price Chart Indicators

Moving Averages Level Buy or Sell
8-day SMA: 17.4 Buy
20-day SMA: 17.07 Buy
50-day SMA: 16.88 Buy
200-day SMA: 16.11 Buy
8-day EMA: 17.45 Buy
20-day EMA: 17.17 Buy
50-day EMA: 16.93 Buy
200-day EMA: 16.37 Buy

First Trust Global Wind Energy ETF Technical Analysis Indicators

Chart Indicators Level Buy or Sell
MACD (12, 26): 0.22 Buy
Relative Strength Index (14 RSI): 68.39 Buy
Chaikin Money Flow: 20210 -
Bollinger Bands Level Buy or Sell
Bollinger Bands (25): (16.7 - 17.38) Buy
Bollinger Bands (100): (16.34 - 17.26) Buy

First Trust Global Wind Energy ETF 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 First Trust Global Wind Energy ETF Stock

Is First Trust Global Wind Energy ETF Stock a Buy?

FAN Technical Analysis vs Fundamental Analysis

Sell
42
First Trust Global Wind Energy ETF (FAN) is a Sell

Is First Trust Global Wind Energy ETF a Buy or a Sell?

First Trust Global Wind Energy ETF Stock Info

Market Cap:
0
Price in USD:
17.79
Share Volume:
20.21K

First Trust Global Wind Energy ETF 52-Week Range

52-Week High:
17.85
52-Week Low:
13.21
Sell
42
First Trust Global Wind Energy ETF (FAN) is a Sell

First Trust Global Wind Energy ETF Share Price Forecast

Is First Trust Global Wind Energy ETF Stock a Buy?

Technical Analysis of First Trust Global Wind Energy ETF

Should I short First Trust Global Wind Energy ETF stock?

* First Trust Global Wind Energy ETF stock forecasts short-term for next days and weeks may differ from long term prediction for next month and year based on timeline differences.