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Koninklijke KPN NV Stock Price Chart

  • Based on the share price being below its 5, 20 & 50 day exponential moving averages, the current trend is considered strongly bearish and KKPNY is experiencing selling pressure, which indicates risk of future bearish movement.

Koninklijke KPN NV Price Chart Indicators

Moving Averages Level Buy or Sell
8-day SMA: 3.78 Sell
20-day SMA: 3.89 Sell
50-day SMA: 4 Sell
200-day SMA: 3.82 Sell
8-day EMA: 3.79 Sell
20-day EMA: 3.87 Sell
50-day EMA: 3.94 Sell
200-day EMA: 3.84 Sell

Koninklijke KPN NV Technical Analysis Indicators

Chart Indicators Level Buy or Sell
MACD (12, 26): -0.07 Sell
Relative Strength Index (14 RSI): 36.52 Sell
Chaikin Money Flow: -240764 -
Bollinger Bands Level Buy or Sell
Bollinger Bands (25): (3.8 - 4.06) Sell
Bollinger Bands (100): (3.88 - 4.1) Sell

Koninklijke KPN NV 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 Koninklijke KPN NV Stock

Is Koninklijke KPN NV Stock a Buy?

KKPNY Technical Analysis vs Fundamental Analysis

Buy
60
Koninklijke KPN NV (KKPNY) is a Buy

Is Koninklijke KPN NV a Buy or a Sell?

Koninklijke KPN NV Stock Info

Market Cap:
14.55B
Price in USD:
3.74
Share Volume:
293.31K

Koninklijke KPN NV 52-Week Range

52-Week High:
4.22
52-Week Low:
3.28
Buy
60
Koninklijke KPN NV (KKPNY) is a Buy

Koninklijke KPN NV Share Price Forecast

Is Koninklijke KPN NV Stock a Buy?

Fundamental Analysis of Koninklijke KPN NV

Is Koninklijke KPN NV a good investment?

  • Analysts estimate an earnings increase this quarter of $0.00 per share, a decrease next quarter of $0.00 per share, an increase this year of $0.05 per share, and an increase next year of $0.01 per share.

Technical Analysis of Koninklijke KPN NV

Should I short Koninklijke KPN NV stock?

* Koninklijke KPN NV stock forecasts short-term for next days and weeks may differ from long term prediction for next month and year based on timeline differences.