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JPMorgan Sustainable Infrastructure 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 BLLD is experiencing slight buying pressure.

JPMorgan Sustainable Infrastructure ETF Price Chart Indicators

Moving Averages Level Buy or Sell
8-day SMA: 54.03 Sell
20-day SMA: 53.05 Buy
50-day SMA: 51.34 Buy
200-day SMA: 48.33 Buy
8-day EMA: 53.89 Sell
20-day EMA: 53.1 Buy
50-day EMA: 51.61 Buy
200-day EMA: 48.78 Buy

JPMorgan Sustainable Infrastructure ETF Technical Analysis Indicators

Chart Indicators Level Buy or Sell
MACD (12, 26): 0.89 Buy
Relative Strength Index (14 RSI): 63.93 Buy
Chaikin Money Flow: 0 -
Bollinger Bands Level Buy or Sell
Bollinger Bands (25): (51.54 - 53.8) Buy
Bollinger Bands (100): (47.65 - 51.79) Buy

JPMorgan Sustainable Infrastructure 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 JPMorgan Sustainable Infrastructure ETF Stock

Is JPMorgan Sustainable Infrastructure ETF Stock a Buy?

BLLD Technical Analysis vs Fundamental Analysis

Buy
80
JPMorgan Sustainable Infrastructure ETF (BLLD) is a Buy

Is JPMorgan Sustainable Infrastructure ETF a Buy or a Sell?

JPMorgan Sustainable Infrastructure ETF Stock Info

Market Cap:
0
Price in USD:
53.78
Share Volume:
22

JPMorgan Sustainable Infrastructure ETF 52-Week Range

52-Week High:
54.62
52-Week Low:
39.55
Buy
80
JPMorgan Sustainable Infrastructure ETF (BLLD) is a Buy

JPMorgan Sustainable Infrastructure ETF Share Price Forecast

Is JPMorgan Sustainable Infrastructure ETF Stock a Buy?

Technical Analysis of JPMorgan Sustainable Infrastructure ETF

Should I short JPMorgan Sustainable Infrastructure ETF stock?

* JPMorgan Sustainable Infrastructure 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.