Video summary
I Stole a Trading Strategy Worth $60 Billion
Main summary
Key takeaways
Finance-focused summary (momentum/trend + volatility-based position sizing)
What the strategy is (from an “AHL” research paper)
- A multi-horizon momentum strategy that uses trend lines.
- It does not forecast direction; it measures the direction of movement that’s already occurring.
- Reported backtest claims:
- Tested on 140 years of data (back to 1880)
- 58 markets
- Positive returns every single decade since 1880
- “Never lost money in any decade” (as stated in the video)
- Robustness claimed across major regimes/crises: wars, depressions, 2008, dot-com bubble, and market crashes
Direction “rating” framework (step-by-step)
A rule-based scoring system assigns a score using multiple time horizons (example uses daily timeframe):
- Draw a trend line from 1 week ago → today
- Uptrend = +1
- Downtrend = -1
- Repeat for:
- 2 weeks ago → today
- 1 month ago → today
- 2 months ago → today
- Add the four scores to get a total score in: {+4, +2, 0, -2, -4}
Map score to trading stance / exposure:
- +4 = fully long
- +2 = half long
- 0 = no trade
- -2 = half short
- -4 = fully short
Position sizing framework (risk + volatility scaling)
The video gives an explicit sizing formula:
- Position sizing = score × target_risk / volatility
Where:
- score: trend score from the framework above
- target_risk: a user-defined risk amount (e.g., % of portfolio) they’re comfortable losing
- Example: $100,000 portfolio risk 10% = $10,000 target risk
- volatility: computed from recent daily returns
- Compute average daily move over 30 days (described as “yesterday close to today close”)
- Example given for Bitcoin (BTC): 2.03% average daily
- Convert daily to annual using × 19.1 (stated as √365)
- 2.03% × 19.1 ≈ 39% annualized volatility
Risk logic emphasized:
- Higher volatility → smaller position size
- Lower volatility → larger position size
- The video claims this is a key reason the strategy “survived” crashes, because sizing contracts during chaos.
Explicit trade executed in the video
The presenter performs a live test trade:
- Long ticker: SCHW (Charles Schwab)
- Scoring outcome for SCHW:
- Trend lines on all four horizons (1 week, 2 weeks, 1 month, 2 months) are upward
- Total score = +4
- Therefore: fully long
- Position sizing outcome:
- Presenter states the computed sizing equals $60,000
- Broker:
- Mentioned as Charles Schwab (using their broker platform)
- Reported performance:
- Entry context: “Wednesday morning came,” and the analysis/editing date is referenced as July 1, 2026
- Results reported later on August 7 (about a little over a month after entry)
- Trade moved up 12%
- Presenter’s P&L: + $7,200
- Profit-taking: exited near/at “all-time highs,” rather than holding longer
Recommendations/cautions and disclosures
- Framed as an experiment (“guinea pig” testing with own money).
- No formal “not financial advice” disclaimer is shown in the provided subtitles.
- Practical cautions implied by the rules:
- No prediction—only trade when the trend score indicates exposure.
- Sizing automatically reduces during high-volatility periods.
- The presenter took profits rather than trying to maximize further gains.
Tickers / assets mentioned
- SCHW — Charles Schwab (the live trade)
- Bitcoin (BTC) — used only as an example for volatility calculation (2.03% daily → ~39% annualized)
- AHL — referenced as the hedge fund/system source of the research model (not a traded ticker in the video context)
Key numbers and timelines
Backtest
- 140 years (from 1880)
- 58 markets
- Claims: positive returns every decade / “never lost money in any decade” (as stated)
Scoring system
- Score outcomes: +4, +2, 0, -2, -4
- Horizons: 1 week, 2 weeks, 1 month, 2 months
Volatility conversion
- Example daily volatility: 2.03%
- Annualization factor: × 19.1 (= √365)
- Example annualized volatility: ~39%
Live trade metrics
- Entry: implied around late June 2026 (edit date referenced as July 1, 2026)
- Results reported: Aug 7, 2026
- Time held: a little over a month
- Price move: +12%
- P&L: +$7,200
Position sizing
- Full exposure example for score +4: $60,000
- Half exposure logic example (score +2 / -2): $30,000 mentioned as conditional logic
Presenters / sources mentioned
- AHL (hedge fund): described as the source of the research paper/model (started 1987, run by computers)
- Presenter of the video (unnamed in subtitles)
- Telegram: where the presenter says a “cheat sheet” is provided (no author named in the subtitles)