XLF — XLF | S&P 500 Financials Sector ETF 13F holdings and portfolio analysis

已就緒XLF | S&P 500 Financials Sector ETF · Michael Riley

登錄後可基於當前選中的策略克隆一個新分支，繼續在新分支裏調整參數與權重。

官方策略
用户分支
返回基金列表

Baseline

分析消息
分支：
Baselinetested
策略問答參考3 條參考問答

基於這隻基金最新一期數據預生成的問答，可直接作為對話上下文使用。

baseline13FChat AI
What does directly following the disclosed baseline portfolio expose an investor to?

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%.

↳Compare baseline concentration risk with the combo equal-weight version side by side.
baseline13FChat AI
Which recent baseline periods best explain the risk-return trade-off?

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.

↳Plot the recent baseline excess-return months from best to worst and explain what likely drove them.
baseline13FChat AI
What should a user inspect next before deciding whether the baseline is acceptable?

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.

↳Decompose the baseline into banks, payments, insurers, brokers, and exchanges to see where the relative risk really sits.
登錄後即可基於上方策略與右側數據，直接與 AI 對話分析。
登錄後開始對話…
可參考左欄策略與右欄數據。