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Playing TSLA & IBM Earnings

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Manage episode 515456152 series 1428227
Content provided by tastylive. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by tastylive or their podcast platform partner. If you believe someone is using your copyrighted work without your permission, you can follow the process outlined here https://podcastplayer.com/legal.
In this episode of From Theory to Practice, Jim Schultz discusses recent earnings trades, particularly focusing on Netflix (NFLX) and upcoming earnings for Tesla (TSLA) and IBM (IBM). He highlights a successful long put spread on Netflix that yielded a profit, emphasizing the effectiveness of at-the-money vertical spreads for earnings plays. Schultz also shares his bullish outlook on Tesla, planning to use an expected move butterfly strategy. For IBM, he opts for an out-of-the-money put spread for a downside bet. The market remains volatile, impacting various assets, including gold and silver.
  continue reading

38 episodes

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Manage episode 515456152 series 1428227
Content provided by tastylive. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by tastylive or their podcast platform partner. If you believe someone is using your copyrighted work without your permission, you can follow the process outlined here https://podcastplayer.com/legal.
In this episode of From Theory to Practice, Jim Schultz discusses recent earnings trades, particularly focusing on Netflix (NFLX) and upcoming earnings for Tesla (TSLA) and IBM (IBM). He highlights a successful long put spread on Netflix that yielded a profit, emphasizing the effectiveness of at-the-money vertical spreads for earnings plays. Schultz also shares his bullish outlook on Tesla, planning to use an expected move butterfly strategy. For IBM, he opts for an out-of-the-money put spread for a downside bet. The market remains volatile, impacting various assets, including gold and silver.
  continue reading

38 episodes

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