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Gabelli Financial Services Opp 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 GABF is experiencing buying pressure, which is a positive indicator for future bullish movement.

Gabelli Financial Services Opp ETF Price Chart Indicators

Moving Averages Level Buy or Sell
8-day SMA: 48.82 Buy
20-day SMA: 47.63 Buy
50-day SMA: 45.32 Buy
200-day SMA: 39.71 Buy
8-day EMA: 48.91 Buy
20-day EMA: 47.85 Buy
50-day EMA: 45.72 Buy
200-day EMA: 40.25 Buy

Gabelli Financial Services Opp ETF Technical Analysis Indicators

Chart Indicators Level Buy or Sell
MACD (12, 26): 1.2 Buy
Relative Strength Index (14 RSI): 72.65 Buy
Chaikin Money Flow: 20006 -
Bollinger Bands Level Buy or Sell
Bollinger Bands (25): (45.55 - 48.91) Buy
Bollinger Bands (100): (39.54 - 45.96) Buy

Gabelli Financial Services Opp 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 Gabelli Financial Services Opp ETF Stock

Is Gabelli Financial Services Opp ETF Stock a Buy?

GABF Technical Analysis vs Fundamental Analysis

Buy
65
Gabelli Financial Services Opp ETF (GABF) is a Buy

Is Gabelli Financial Services Opp ETF a Buy or a Sell?

Gabelli Financial Services Opp ETF Stock Info

Market Cap:
0
Price in USD:
49.78
Share Volume:
20.01K

Gabelli Financial Services Opp ETF 52-Week Range

52-Week High:
49.78
52-Week Low:
30.80
Buy
65
Gabelli Financial Services Opp ETF (GABF) is a Buy

Gabelli Financial Services Opp ETF Share Price Forecast

Is Gabelli Financial Services Opp ETF Stock a Buy?

Technical Analysis of Gabelli Financial Services Opp ETF

Should I short Gabelli Financial Services Opp ETF stock?

* Gabelli Financial Services Opp 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.