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Invesco KBW Property & Casualty Ins 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 KBWP is experiencing slight buying pressure.

Invesco KBW Property & Casualty Ins ETF Price Chart Indicators

Moving Averages Level Buy or Sell
8-day SMA: 120.36 Buy
20-day SMA: 117.65 Buy
50-day SMA: 116.43 Buy
200-day SMA: 107.79 Buy
8-day EMA: 119.95 Buy
20-day EMA: 118.33 Buy
50-day EMA: 116.16 Buy
200-day EMA: 107.74 Buy

Invesco KBW Property & Casualty Ins ETF Technical Analysis Indicators

Chart Indicators Level Buy or Sell
MACD (12, 26): 1.38 Buy
Relative Strength Index (14 RSI): 63.3 Buy
Chaikin Money Flow: 7197 -
Bollinger Bands Level Buy or Sell
Bollinger Bands (25): (115.3 - 120.32) Buy
Bollinger Bands (100): (106.45 - 117.59) Buy

Invesco KBW Property & Casualty Ins 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 Invesco KBW Property & Casualty Ins ETF Stock

Is Invesco KBW Property & Casualty Ins ETF Stock a Buy?

KBWP Technical Analysis vs Fundamental Analysis

Buy
60
Invesco KBW Property & Casualty Ins ETF (KBWP) is a Buy

Is Invesco KBW Property & Casualty Ins ETF a Buy or a Sell?

Invesco KBW Property & Casualty Ins ETF Stock Info

Market Cap:
0
Price in USD:
121.47
Share Volume:
30.3K

Invesco KBW Property & Casualty Ins ETF 52-Week Range

52-Week High:
122.12
52-Week Low:
88.03
Buy
60
Invesco KBW Property & Casualty Ins ETF (KBWP) is a Buy

Invesco KBW Property & Casualty Ins ETF Share Price Forecast

Is Invesco KBW Property & Casualty Ins ETF Stock a Buy?

Technical Analysis of Invesco KBW Property & Casualty Ins ETF

Should I short Invesco KBW Property & Casualty Ins ETF stock?

* Invesco KBW Property & Casualty Ins 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.