XLF — XLF | S&P 500 Financials Sector ETF 13F holdings and portfolio analysis
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Baseline
Analysis messagesPre-generated Q&A about this fund. Use as reference context for your own analysis.
Directly following the baseline exposes an investor to a concentrated all-Financials bet with meaningful stock-specific risk. In the baseline artifact, sectorWeights are 100.03% Financials and concentration is high with top5 at 41.21%, top10 at 56.27%, and top20 at 72.63%. The largest positions are BRK.A 11.76%, JPM 11.19%, V 7.56%, MA 5.98%, and BAC 4.72%, so a handful of franchises drive outcomes. Backtest risk metrics reinforce that concentration cost: beta is 1.03, maxDrawdown is -43.21, and the baseline risk notes warn that top five holdings exceed 41% and volatility was above 22%.
Recent baseline periods show a mix of modest alpha wins offset by several sharper underperformance bursts. The strongest positive excess months were 2025-11-30 at +3.72, 2025-01-31 at +2.02, and 2025-10-31 at +1.53. But the weak side was more damaging in several recent stretches: 2025-09-30 posted -5.19 excess, 2025-08-31 was -2.53, and 2025-06-30 was -2.23. Even though 2025-12-31 is flat at 0.00 for both, the pattern across these periods helps explain why the baseline still shows negative alpha (-0.69) despite a 12.37% annualized return: it compounded well absolutely, but its bad relative months were too frequent and too deep.
A user should inspect three things next: concentration, implementation friction, and the exact role of bank exposure within Financials. Baseline concentration is already high at top5 41.21% and top10 56.27%, so the first check is whether that is acceptable relative to your own diversification threshold. Second, the backtest is operationally heavy, with 8,257 trades and totalEstimatedCost 1.0209, so you should verify whether reported-holdings replication is practical after lag and costs. Third, recent period results show several negative excess months—especially 2025-09-30 at -5.19 and 2025-08-31 at -2.53—so the next step is identifying whether those losses came mainly from banks like BAC, WFC, C, and JPM or from the broader payments/insurance mix.