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Actionable insights — September 2026 Portfolio Update

Not which stocks he holds, but how he turns a portfolio into a ranked list of expected returns, decides where new money goes, and places each holding on an AI-cycle timeline.
2026-SEP-05 · Qualtrim Studio — Portfolio Updates · Joseph Carlson (solo) · ▶ Watch on Qualtrim · full analysis · transcript
How to read this page: each insight is a reusable procedure. The boxed line shows how it played out in this update. Timestamps are positions in the login-gated Qualtrim Studio recording (the link opens the video).

21:01 1. Give every holding a five-year expected return and a hurdle

The repeatable method
  1. Estimate compounded EPS growth for five years (earnings, not revenue, if heavy investment will be amortized).
  2. Pick a defensible exit P/E for the business quality.
  3. Solve the implied annual return from today's price; also solve the price that would deliver your hurdle (here 15%).
  4. Aim for "accurate, not conservative or aggressive" inputs; treat the output as directional.
Here: META 13% × 24× → 18.14%, 15% entry at $677; GOOGL 15% × 25× → 9.6%; COST 12% × 33× → 5.47%.
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1:11:24 2. Steer new money by expected return; don't churn the book

The repeatable method
  1. Rank all holdings by expected return.
  2. Direct fresh cash to the top names; let below-hurdle names become holds.
  3. Trim only when a great company's price far exceeds your fair value, and keep a foot in the door.
  4. Respect friction, taxes, concentration and risk-factor overlap before any sale.
Here: New buys go to META/UBER/NFLX; COST and TXRH are held without adds; ASML is the only trim (20%, fair value ~$1,300–1,400 vs ~$2,000).
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1:12:14 3. Run a clean-slate allocation to test your conviction

The repeatable method
  1. Pretend you own nothing and have a fixed sum.
  2. Weight toward the highest expected returns but diversify across the next tier rather than going all-in.
  3. Compute the weighted expected return and compare it with your actual portfolio's mix.
Here: $10k: META 30%, UBER 20%, NFLX 15%, MA 12.5%, AMZN 10%, SPGI 7.5%, MSFT 5% → 15.95% weighted; GOOGL, his largest actual position, gets nothing.
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8:37 4. Map each holding onto the phases of a technology cycle

The repeatable method
  1. Define the phases: build (suppliers), monetization (buyers turn it into revenue), distribution, commoditization, durable ownership of the customer.
  2. Label each holding by the phase in which it earns the most.
  3. Be early for the later phases (markets price them ahead) and be most careful holding build-phase suppliers into commoditization.
Here: Build-phase NVDA/memory/power won 2023–26; he tilts to GOOGL, AMZN, META, NFLX, UBER as aggregators that own demand into 2028–32.
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56:51 5. Compare competitors' strategies for the same threat — aggregate vs build

The repeatable method
  1. For a disruptive technology, list what each incumbent is doing: partnering/aggregating or building in-house.
  2. Weigh the aggregator's capital-light reach against the builder's control and cost.
  3. Look for real deployments ("wheels on the ground"), not partnership announcements.
Here: UBER aggregates (Wayve in London, 2,000+ European robotaxis, Zipline drones); DASH builds (Part 135 drones, Dot robots in a high single digit % of test-market orders). He owns both, prefers Uber on price.
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2:53 6. Measure yourself on time-weighted returns and multi-year win rates

The repeatable method
  1. Report all-in gains including every sale at a loss and dividends, not just current holdings.
  2. Use time-weighted return so deposit timing doesn't flatter or punish results.
  3. Judge underperformance years against a realistic win rate; check whether holdings' fundamentals (revenue growth) are still compounding.
Here: $528k gains, 200% time-weighted; flat YTD vs S&P +12%; Berkshire beat the index in only ~66% of years; holdings still growing revenue ~16%.
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Methods distilled from the login-gated Qualtrim Studio video for personal study. Not investment advice.