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Friday, December 5, 2025

PSW’s Weekly Webinar: 101 Days and I’m Exhausted!

101 Days and I'm Exhausted! (4/30/2025)

Timeline:

0:00 – Reaction to bad GDP report
0:53 – Demonstration of Google NotebookLM and AI tools
2:59 – AI summarizing earnings and finding trends
7:00 – Discussion on EPS beats and lowered expectations
10:04 – AI limitations on historical data access
12:23 – Mixed revenue results and cautious guidance
18:02 – Earnings previews
21:05 – Trade ideas and risk analysis for major tech earnings
25:28 – AI-related capital expenditures and tariffs
30:30 – S&P analysis and earnings expectations
34:03 – Ferrari example and impact of U.S. policy instability
39:05 – Reversal risk and factory planning disincentives
43:20 – Corporate uncertainty under Trump’s tariffs
46:22 – Tariff impact on clean energy and investments
49:01 – Breakdown of U.S. institutional instability
53:06 – Historical market comparisons and risk of collapse
57:40 – Earnings summary and macroeconomic trends
1:06:04 – Drill Baby Drill and U.S. energy independence
1:13:00 – U.S. loss of reputation and legal uncertainty
1:20:01 – Historical comparisons 
1:23:00 – Sector performance snapshot
1:26:11 – Presidential history and market reactions
1:31:03 – S&P technical breakdown and resistance
1:34:01 – Risk/reward trade-off vs. 10-year bond yield
1:38:03 – Profit margins, inflation, and earnings growth
1:42:01 – Price hikes and corporate strategy
1:46:08 – Media pressure and Trump’s influence
1:50:00 – Global market risks and diversification
1:53:00 – Hedging strategies and current positioning
2:00:05 – Historical perspective and strategy for collapse
2:06:40 – Wrap-up and sign off

*****

Summary of the Stock Market and Earnings Webinar

The webinar begins with Phil discussing the disappointing GDP report. Although the data came in weak, it was widely expected, so the market's reaction was relatively muted (April 30). Most major indexes were down around 1%, except for the Dow, which was slightly supported by UnitedHealth’s strong performance.

Phil then walks through how he uses Google’s Notebook LM to analyze large volumes of earnings data pulled from briefing.com.

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