Sequoia Fund, Inc. 13F holdings and portfolio analysis

Directly following the baseline exposes an investor to a highly top-heavy portfolio with meaningful single-name and sector-bucket risk. In the strategy artifact, the top 5 holdings are 53.73% and the top 10 are 82.86%, with GOOGL alone at 16.2%, COF at 10.46%, ELV at 9.75%, SCHW at 8.73%, and ICE at 8.59%. Sector exposure is concentrated in Financials at 34.6%, Health Care at 24.24%, and Communication Services at 21.27%. That structure produced 11.48% annualizedReturn and 184.01% totalReturn, but it also came with -34.68% maxDrawdown, negative alpha of -0.69, and 617 trades with totalEstimatedCost of 1.9681 under filing-lag implementation.

Three recent periods explain the baseline trade-off well. First, 2023-03-31 shows the upside case: optimizedReturn was 13.38% versus benchmarkReturn 7.9%, for +5.47% excess with only 12.02 turnover. Second, 2025-03-31 shows the downside of lagged concentration: optimizedReturn was just 1.8% versus 9.22% for SPY, a -7.42% excess shortfall with 16.6 turnover. Third, 2025-09-30 shows that the strategy can still recover strongly when its stock selection works, with optimizedReturn 7.06% versus 1.49% for SPY, or +5.57% excess. These swings help explain why the baseline has decent absolute return but only a 0.67 Sharpe and negative alpha overall.

A user should inspect concentration, turnover, and filing-lag sensitivity next. The baseline artifact shows top5 concentration of 53.73% and top10 of 82.86%, so the first check is whether those weights are acceptable. The second is implementation friction: turnover reached 25.84 in 2022-12-31, 23.13 in 2023-06-30, and 22.05 in 2024-09-30, while the artifact also warns of 617 trades and totalEstimatedCost of 1.9681. The third is whether the investor can tolerate downside behavior, because maxDrawdown was -34.68% and recoveryDays were 107. If those three dimensions are not acceptable, the baseline may not fit even though headline annualizedReturn was 11.48%.