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SNMP | Sanchez Midstream Partners LP

Sanchez Midstream Partners LP

    Quick infos

    • Headquarters:   Houston, Texas, United States

    Trade prices

    • Volume:
    • Market Cap: 67.01M
    • Prev closed: 1.12
    • Open: 1.14
    • High: 1.14
    • Low: 1.01
    • 52 week low: 0.2
    • 52 week high: 1.77
    • Dividends:

    Next ER: May 19, 2022  Before Market Opens



    Top Stories (SNMP)

      Earnings History

      Date EPS / Forecast Revenue / Forecast
      August 11, 2022
      May 19, 2022-2.06 / -- / -
      March 25, 2022-2.06 / -16.18M / -Beat!
      November 16, 2021-2.06 / -16.87M / -Beat!
      August 12, 2021-2.06 / -9.14M / -Beat!
      view more

      Historical Data

      DatePriceOpenHighLowVolChangeER
      May 19, 2022 0.4561 0.4400
      0.4698
      0.4359
      287.05K -2.96%
      May 18, 2022 0.4700 0.4806
      0.4897
      0.4400
      271.31K -3.85%
      May 17, 2022 0.4888 0.4831
      0.4889
      0.4512
      381.99K 1.12%
      May 16, 2022 0.4834 0.4365
      0.5355
      0.4302
      930.58K 7.42%
      May 13, 2022 0.4500 0.4199
      0.4500
      0.4121
      466.82K 9.86%
      May 12, 2022 0.4096 0.4063
      0.4280
      0.3829
      375.23K 3.83%
      May 11, 2022 0.3945 0.4030
      0.4297
      0.3900
      493.58K -1.38%
      May 10, 2022 0.4000 0.4200
      0.4600
      0.4000
      479.32K -1.94%
      May 9, 2022 0.4079 0.4266
      0.4266
      0.3900
      852.70K -6.51%
      May 6, 2022 0.4363 0.4400
      0.4700
      0.4287
      493.34K -3.02%
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      NYSE - New York Stock Exchange


      SNMP Dividends

      Ex-Dividend Amount Announced Date Record Date Payment Date
      May 21, 20190.15May 31, 2019
      Feb 19, 20190.15Feb 28, 2019
      Nov 19, 20180.15Nov 30, 2018
      Aug 20, 20180.4508Aug 31, 2018
      May 21, 20180.4508May 31, 2018
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      EarningsAhead is not affiliated with and this is not an endorsement of the companies featured above.
      This profile is based on publicly available information and is intended to be informative in nature.

      Most of the datas are collected by our Data Entry and we aim to be as accurate as humanly possible.




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