Lindsell Train Limited 13F holdings and portfolio analysis

Following the baseline directly exposes an investor to an extremely top-heavy U.S.-listed replica rather than a balanced multi-name portfolio. In the baseline strategy artifact, the top 5 holdings are 63.13% and the top 10 are 96.68%, led by Alphabet at 16.89%, TKO at 15.22%, Intuit at 10.45%, Thermo Fisher at 10.33%, and Disney at 10.24%. Sector weights are also concentrated, with 43.85% in Communication Services and 20.04% in Information Technology. That structure helped produce 12.13% annualized return and positive 1.79 alpha, but it also left the portfolio with a -31.37% max drawdown and a risk note that turnover hit 93.8% in one period.

The recent baseline periods that best explain the trade-off are the ones where modest excess return came with meaningful turnover and uneven benchmark capture. The strongest recent relative periods were 2024-12-31, when optimizedReturn was 0.77% versus benchmarkReturn of -3.63% for +4.40% excess, and 2022-12-31, when optimizedReturn was 3.85% versus -0.25% for +4.10% excess. But weak stretches were also clear: 2025-03-31 delivered 4.08% versus SPY’s 9.22% for -5.14% excess, and 2024-09-30 returned -1.99% versus 2.76% for -4.75% excess. Turnover was not trivial in those periods either, reaching 23.36 at 2024-12-31 and 16.56 at 2024-09-30, which helps explain why the baseline could still feel unstable despite lower beta of 0.79.

A user should inspect three things next: concentration, sector dependence, and trade timing. Concentration is the first screen because the baseline top 10 already represent 96.68% of assets and the top 5 are 63.13%. Sector dependence comes next because Communication Services alone is 43.85%, with another 20.04% in Information Technology and 14.13% in Consumer Staples. Finally, trade timing matters because the artifact warns about 13F-style disclosure lag and notes a period with 93.8% turnover, meaning live implementation may differ materially from the backtest. Those checks matter more here than small metric differences because the optimized and original baseline results were identical according to the risk notes.