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Guinness Atkinson Sustainable Energy ETF Stock Price Chart

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

Guinness Atkinson Sustainable Energy ETF Price Chart Indicators

Moving Averages Level Buy or Sell
8-day SMA: 31.35 Sell
20-day SMA: 30.96 Buy
50-day SMA: 31.33 Sell
200-day SMA: 28 Buy
8-day EMA: 31.25 Sell
20-day EMA: 31.21 Sell
50-day EMA: 31.04 Sell
200-day EMA: 29.05 Buy

Guinness Atkinson Sustainable Energy ETF Technical Analysis Indicators

Chart Indicators Level Buy or Sell
MACD (12, 26): 0.04 Buy
Relative Strength Index (14 RSI): 47.69 Sell
Chaikin Money Flow: 0 -
Bollinger Bands Level Buy or Sell
Bollinger Bands (25): ( - ) Buy
Bollinger Bands (100): ( - ) Buy

Guinness Atkinson Sustainable 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 Guinness Atkinson Sustainable Energy ETF Stock

Is Guinness Atkinson Sustainable Energy ETF Stock a Buy?

SOLR Technical Analysis vs Fundamental Analysis

Buy
53
Guinness Atkinson Sustainable Energy ETF (SOLR) is a Buy

Is Guinness Atkinson Sustainable Energy ETF a Buy or a Sell?

Guinness Atkinson Sustainable Energy ETF Stock Info

Market Cap:
0
Price in USD:
31.01
Share Volume:
25

Guinness Atkinson Sustainable Energy ETF 52-Week Range

52-Week High:
32.93
52-Week Low:
20.69
Buy
53
Guinness Atkinson Sustainable Energy ETF (SOLR) is a Buy

Guinness Atkinson Sustainable Energy ETF Share Price Forecast

Is Guinness Atkinson Sustainable Energy ETF Stock a Buy?

Technical Analysis of Guinness Atkinson Sustainable Energy ETF

Should I short Guinness Atkinson Sustainable Energy ETF stock?

* Guinness Atkinson Sustainable 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.