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Saipem SpA Stock Predictions

Saipem SpA Stock Forecast

  • Is Saipem SpA Stock Undervalued?
    The current Saipem SpA [SAPMY] share price is $0.42. The Score for SAPMY is 55, which is 10% above its historic median score of 50, and infers lower risk than normal.
  • SAPMY is currently trading in the 50-60% percentile range relative to its historical Stock Score levels.

Will Saipem SpA Stock Go Up Next Year?

Data Unavailable

Saipem SpA Stock Rating

Data Unavailable

Saipem SpA Stock Price History

Is SAPMY stock going to rise?

  • Based on the share price being below its 5, 20 & 50 day exponential moving averages, the current trend is considered strongly bearish and SAPMY is experiencing slight buying pressure.

Stock Information

Stock Info

Exchange:
OTCM
Country:
Italy
Industry:
Energy Equipment & Services
Sector:
Energy
Type:
stock
Website:
saipem.com

52-Week Data

52-Week High:
0.52
52-Week Low:
0.22

Prediction Charts

Market Cap:
43.27M
Price in USD:
0.42
Volume:
5.75K
Beta:
2.00

Technical Analysis

SMA50:
0.43
SMA100:
0.44
SMA200:
0.41
52-Wk Change:
51.26%

Stock Predictions

  • Is Saipem SpA stock public?
    Yes, Saipem SpA is a publicly traded company.
  • What is the Saipem SpA stock quote today?
    The Saipem SpA stock price is 0.42 USD today.
  • How to buy Saipem SpA stock online?
    You can buy Saipem SpA shares by opening an account at a top tier brokerage firm, such as TD Ameritrade or tastyworks.

14-Day Historical Data

Date Opening Closing Minimum Maximum
Sep-27 0.44 0.44 0.44 0.44
Sep-30 0.44 0.44 0.44 0.44
Oct-1 0.44 0.44 0.44 0.44
Oct-2 0.39 0.45 0.45 0.39
Oct-3 0.45 0.45 0.45 0.45
Oct-4 0.45 0.45 0.45 0.45
Oct-7 0.45 0.45 0.45 0.45
Oct-8 0.45 0.45 0.45 0.45
Oct-9 0.45 0.45 0.45 0.45
Oct-10 0.48 0.48 0.48 0.48
Oct-11 0.48 0.48 0.48 0.48
Oct-14 0.35 0.35 0.35 0.35
Oct-15 0.35 0.35 0.35 0.35
Oct-16 0.42 0.42 0.42 0.42

Saipem SpA Earnings

Data Unavailable

Saipem SpA Forecast Revenue Growth

Data Unavailable

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