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FIS Knights of Columbus Global Blf ETF Stock Price Chart

Buy
72

KOCG
FIS Knights of Columbus Global Blf ETF

Last Price:
26.14
Seasonality Move:
0.18%

7 Day Trial

ALL ACCESS PASS

$ 7
  • The current trend is moderately bullish and KOCG is experiencing slight buying pressure.

FIS Knights of Columbus Global Blf ETF Price Chart Indicators

Moving Averages Level Buy or Sell
8-day SMA: 26.18 Buy
20-day SMA: 26 Buy
50-day SMA: 25.52 Buy
200-day SMA: 23.81 Buy
8-day EMA: 26.18 Buy
20-day EMA: 26 Buy
50-day EMA: 25.65 Buy
200-day EMA: 24.2 Buy

FIS Knights of Columbus Global Blf ETF Technical Analysis Indicators

Chart Indicators Level Buy or Sell
MACD (12, 26): 0.19 Buy
Relative Strength Index (14 RSI): 63.28 Buy
Chaikin Money Flow: 0 -
Bollinger Bands Level Buy or Sell
Bollinger Bands (25): (25.78 - 26.18) Buy
Bollinger Bands (100): (24.51 - 25.85) Buy

FIS Knights of Columbus Global Blf 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 FIS Knights of Columbus Global Blf ETF Stock

Is FIS Knights of Columbus Global Blf ETF Stock a Buy?

KOCG Technical Analysis vs Fundamental Analysis

Buy
72
FIS Knights of Columbus Global Blf ETF (KOCG) is a Buy

Is FIS Knights of Columbus Global Blf ETF a Buy or a Sell?

FIS Knights of Columbus Global Blf ETF Stock Info

Market Cap:
0
Price in USD:
26.35
Share Volume:
34

FIS Knights of Columbus Global Blf ETF 52-Week Range

52-Week High:
26.40
52-Week Low:
20.76
Buy
72
FIS Knights of Columbus Global Blf ETF (KOCG) is a Buy

FIS Knights of Columbus Global Blf ETF Share Price Forecast

Is FIS Knights of Columbus Global Blf ETF Stock a Buy?

Technical Analysis of FIS Knights of Columbus Global Blf ETF

Should I short FIS Knights of Columbus Global Blf ETF stock?

* FIS Knights of Columbus Global Blf 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.