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Friday, January 9, 2026

PSW’s Weekly Webinar: Kicking off 2026 with our $700 Month Portfolio Review!

Kicking off 2026 with our $700 Month Portfolio Review! (1-7-26)

Timeline

0:00 – Natural gas spike and pivot points basics 
1:34 – Oil move; EIA data delays / shutdown effects
5:36 – Refinery utilization limits; Venezuela oil math
7:16 – Heavy crude mismatch; global refining constraints
8:55 – Venezuela strategy: refining locally vs US risks
11:26 – Trump infrastructure reimbursement proposal
13:08 – Why subsidizing oil companies makes no sense
14:54 – US oil depletion, energy policy, renewables rollback
18:29 – Market indices at highs; technical support levels
20:24 – Hedging rationale (politics, shutdowns, tariffs)
22:38 – Magnificent 7 valuations overview
23:35 – Nvidia outlook; cooling, data centers, capex rethink
26:53 – Tesla valuation critique and short thesis
29:56 – Upcoming macro data and earnings season
31:36 – MAG 7 capex vs profits; dot-com comparison
35:15 – AI reality check; AGI hype vs real capability
41:06 – Using AI tools; CDC data example
44:10 – CES robot demos; realism vs hype
47:38 – Dot-com/Pets.com adoption lessons
50:22 – Shift to $700/month portfolio + Q&A
51:39 – HLE earnings trade: selling premium logic
1:04:32 – SoFi position review (hold; remaining upside)
1:13:14 – Micron (MU) position timing discussion
1:13:49 – Freeport-McMoRan (FCX) channel behavior
1:19:46 – Portfolio-wide review begins
1:31:09 – Cash as hedge; deploying on market dips
1:34:00 – Novo Nordisk spread (“free trade” concept)
1:36:28 – PR spread income strategy
1:38:22 – SQQQ hedge mechanics
1:42:22 – Valet exit and lessons learned
1:46:03 – Portfolio philosophy: boring, undervalued, premium-selling
1:47:23 – $700/month compounding to $1M framework
1:52:42 – Conservative vs “fun money” portfolios
1:56:39 – How Phil chooses strikes for income trades
1:57:16 – Why ARCC was added
1:57:46 – Wrap-up 

Summary

Phil’s webinar moved fluidly between energy, markets, and trading mechanics, but the unifying theme was discipline: understanding how real-world systems actually work, and structuring trades to exploit probability rather than narrative.

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