• Information Technology37.50%
• Communication Services25.00%
• Financials12.50%
• Consumer Discretionary12.50%
• Consumer Staples12.50%

• NVDANVIDIA Corporation12.50% (-3.11)
• MSFTMicrosoft Corporation12.50% (+0.12)
• GOOGLAlphabet Inc.12.50% (+6.48)
• METAMeta Platforms, Inc.12.50% (+7.93)
• PLTRPalantir Technologies Inc.12.50% (+10.41)
• JPMJPMorgan Chase & Co.12.50% (+7.99)
• AMZNAmazon.com, Inc.12.50% (+8.02)
• COSTCostco Wholesale Corporation12.50% (+10.53)

vs Baseline: Annualized +10.05 · Alpha +7.72 · Sharpe +0.26

• combo13FChat AI

  How did the combo equal-weight screen change portfolio structure versus the baseline?

  The combo equal-weight screen reduced single-name dominance but still stayed concentrated in eight names at 12.5% each. It kept NVDA, MSFT, GOOGL, META, PLTR, JPM, AMZN, and COST, versus the baseline’s market-cap-like concentration led by NVDA at 15.61%, AAPL at 13.84%, and MSFT at 12.38%. The combo screen removed AAPL and several smaller defensive names, while sharply increasing PLTR (+10.41 points), COST (+10.53), AMZN (+8.02), JPM (+7.99), META (+7.93), and GOOGL (+6.48). Sector exposure became 37.5% Information Technology, 25.0% Communication Services, 12.5% Financials, 12.5% Consumer Discretionary, and 12.5% Consumer Staples.

  strategyViews.combo-equal-screen.topHoldingsstrategyViews.combo-equal-screen.latestChangesstrategyViews.combo-equal-screen.sectorWeightsstrategyViews.baseline.topHoldings

  ↳ Show which baseline names were replaced or downweighted by the combo equal-weight screen and why that matters.

• combo13FChat AI

  Was the combo screen's result driven more by stock selection or by weight redistribution?

  The result appears to be driven by both, but weight redistribution was a major contributor because the screen equal-weighted eight selected names and massively lifted several smaller baseline positions. PLTR rose from 2.09% to 12.5%, COST from 1.97% to 12.5%, AMZN from 4.48% to 12.5%, JPM from 4.51% to 12.5%, and META from 4.57% to 12.5%, while NVDA was actually reduced from 15.61% to 12.5%. That redistribution coincided with much better results: annualized return improved to 34.72%, alpha to 12.69, and total return to 41.08%. So the screen did not just pick winners; it also gave materially more weight to several non-dominant baseline names.

  strategyViews.combo-equal-screen.topHoldingsstrategyViews.combo-equal-screen.metricsstrategyViews.combo-equal-screen.metricDelta

  ↳ Decompose the combo screen’s outperformance into stock-selection effects versus equal-weight reallocation effects.

• combo13FChat AI

  What trade-off should a user understand before choosing the combo equal-weight screen?

  The main trade-off is accepting a concentrated, growth-tilted active basket for stronger backtested returns. The combo screen improved annualized return to 34.72%, alpha to 12.69, and Sharpe to 1.39, all better than baseline. But it still carries meaningful risk: top 5 concentration is 62.5%, beta is 1.14, and max drawdown is -22.83%, slightly worse than the baseline’s -21.61%. It also remains dependent on a narrow set of leaders such as NVDA, MSFT, GOOGL, META, PLTR, and AMZN, even though equal weighting reduces the baseline’s reliance on a single mega-cap.

  strategyViews.combo-equal-screen.metricsstrategyViews.combo-equal-screen.concentrationstrategyViews.combo-equal-screen.topHoldingsstrategyViews.baseline.metrics

  ↳ Show whether the combo screen still works if I cap tech-platform exposure or reduce the number of equal-weight names.