XLK — XLK | S&P 500 Technology Sector ETF 13F holdings and portfolio analysis

已就緒XLK | S&P 500 Technology 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 means accepting a highly concentrated technology portfolio with benchmark-beating return potential but clear single-name and sector dependence. Top 5 concentration is 48.92%, top 10 is 62.49%, and sectorWeights show essentially all exposure in Information Technology in the baseline artifact. The top positions are NVDA 14.94%, AAPL 13.25%, and MSFT 11.85%, so portfolio outcomes are heavily driven by a few mega-cap tech leaders. Backtest metrics show 21.98% annualized return and 4.83 alpha, but also 1.26 beta and -34.02% max drawdown.

Show me what the baseline would look like if I capped each holding at 10% without changing the rest of the weights.
baseline13FChat AI
Which recent baseline periods best explain the risk-return trade-off?

The recent baseline trade-off is best illustrated by the sharp rebound months and the weak selloff months. Strong periods include 2025-04 with +9.91% return versus SPY’s +6.28%, 2025-05 with +7.76% versus +3.75%, and 2025-09 with +6.53% versus +2.05%. But the downside is visible in 2025-02 at -8.51% and 2025-10 at -4.84%, the latter lagging SPY by -5.04 percentage points. Those swings fit the baseline’s 1.26 beta and -34.02% max drawdown profile: strong upside participation in risk-on tech periods, but painful underperformance in sharp reversals.

Rank the baseline’s last 12 monthly periods by excess return versus SPY and mark which ones had the highest turnover.
baseline13FChat AI
What should a user inspect next before deciding whether the baseline is acceptable?

A user should inspect three things next: concentration, drawdown path, and implementation cost. Concentration is elevated with top 5 at 48.92% and top 10 at 62.49%, so it is important to decide whether that level of top-heavy risk is acceptable. The drawdown path matters because baseline max drawdown reached -34.02% and recovery took 189 days. Implementation also matters because the baseline run used 8,483 trades with totalEstimatedCost of 2.7013, even though the artifact notes baseline and optimized results are identical and offered no improvement from optimization.

Show me the worst peak-to-trough periods in the baseline NAV and the trades executed around those dates.
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。