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Service Properties Trust 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 SVC is experiencing slight buying pressure.

Service Properties Trust Price Chart Indicators

Moving Averages Level Buy or Sell
8-day SMA: 2.01 Buy
20-day SMA: 1.9 Buy
50-day SMA: 2.29 Sell
200-day SMA: 3.3 Sell
8-day EMA: 2.03 Buy
20-day EMA: 2.01 Buy
50-day EMA: 2.2 Buy
200-day EMA: 3.31 Sell

Service Properties Trust Technical Analysis Indicators

Chart Indicators Level Buy or Sell
MACD (12, 26): -0.04 Sell
Relative Strength Index (14 RSI): 59.85 Buy
Chaikin Money Flow: 835878 -
Bollinger Bands Level Buy or Sell
Bollinger Bands (25): (1.8 - 2.02) Buy
Bollinger Bands (100): (2.09 - 2.83) Sell

Service Properties Trust 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 Service Properties Trust Stock

Is Service Properties Trust Stock a Buy?

SVC Technical Analysis vs Fundamental Analysis

Sell
37
Service Properties Trust (SVC) is a Sell

Is Service Properties Trust a Buy or a Sell?

Service Properties Trust Stock Info

Market Cap:
373.3M
Price in USD:
2.24
Share Volume:
3.1M

Service Properties Trust 52-Week Range

52-Week High:
6.34
52-Week Low:
1.71
Sell
37
Service Properties Trust (SVC) is a Sell

Service Properties Trust Share Price Forecast

Is Service Properties Trust Stock a Buy?

Fundamental Analysis of Service Properties Trust

Is Service Properties Trust a good investment?

  • Analysts estimate an earnings decrease this quarter of $0.00 per share, a decrease next quarter of $0.00 per share, a decrease this year of $1.05 per share, and an increase next year of $0.16 per share.

Technical Analysis of Service Properties Trust

Should I short Service Properties Trust stock?

* Service Properties Trust stock forecasts short-term for next days and weeks may differ from long term prediction for next month and year based on timeline differences.