Financhill
Back

BMO Global High Dividend Cvrd Call 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 ZWG.TO is experiencing slight buying pressure.

BMO Global High Dividend Cvrd Call ETF Price Chart Indicators

Moving Averages Level Buy or Sell
8-day SMA: 31.29 Buy
20-day SMA: 31.09 Buy
50-day SMA: 30.9 Buy
200-day SMA: 30.05 Buy
8-day EMA: 31.31 Buy
20-day EMA: 31.12 Buy
50-day EMA: 30.88 Buy
200-day EMA: 30.09 Buy

BMO Global High Dividend Cvrd Call ETF Technical Analysis Indicators

Chart Indicators Level Buy or Sell
MACD (12, 26): 0.17 Buy
Relative Strength Index (14 RSI): 61.48 Buy
Chaikin Money Flow: 463 -
Bollinger Bands Level Buy or Sell
Bollinger Bands (25): (30.85 - 31.33) Buy
Bollinger Bands (100): (30.04 - 31.02) Buy

BMO Global High Dividend Cvrd Call 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 BMO Global High Dividend Cvrd Call ETF Stock

Is BMO Global High Dividend Cvrd Call ETF Stock a Buy?

ZWG.TO Technical Analysis vs Fundamental Analysis

Sell
40
BMO Global High Dividend Cvrd Call ETF (ZWG.TO) is a Sell

Is BMO Global High Dividend Cvrd Call ETF a Buy or a Sell?

BMO Global High Dividend Cvrd Call ETF Stock Info

Market Cap:
0
Price in USD:
31.45
Share Volume:
1.85K

BMO Global High Dividend Cvrd Call ETF 52-Week Range

52-Week High:
31.58
52-Week Low:
26.84
Sell
40
BMO Global High Dividend Cvrd Call ETF (ZWG.TO) is a Sell

BMO Global High Dividend Cvrd Call ETF Share Price Forecast

Is BMO Global High Dividend Cvrd Call ETF Stock a Buy?

Technical Analysis of BMO Global High Dividend Cvrd Call ETF

Should I short BMO Global High Dividend Cvrd Call ETF stock?

* BMO Global High Dividend Cvrd Call 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.