Baseline
Track disclosed holdings with the standard reporting lag and no active reweighting.
AI Summary
High-conviction large-growth portfolio with strong long-run excess returns, but extreme concentration drives stock-specific risk.
Portfolio Snapshot
Current optimized weights for the selected default session.
| Symbol | Name | Sector | Weight | Diff |
|---|---|---|---|---|
| AAPL | Apple Inc. | Information Technology | 51.42% | 0 |
| BRK.A | Berkshire Hathaway Inc. | Financials | 21.09% | 0 |
| NVDA | NVIDIA Corporation | Information Technology | 7.89% | 0 |
| PDD | PDD Holdings Inc. | Consumer Discretionary | 7.65% | 0 |
| GOOGL | Alphabet Inc. | Communication Services | 3.40% | 0 |
| OXY | Occidental Petroleum Corporation | Energy | 3.17% | 0 |
| MSFT | Microsoft Corporation | Information Technology | 2.43% | 0 |
| BABA | Alibaba Group Holding Limited | Consumer Discretionary | 2.20% | 0 |
| DIS | The Walt Disney Company | Communication Services | 0.47% | 0 |
| CRWV | CoreWeave, Inc. | Information Technology | 0.12% | 0 |
| CRDO | Credo Technology Group Holding Ltd | Information Technology | 0.12% | 0 |
| TEM | Tempus AI, Inc. | Health Care | 0.04% | 0 |
Sector Exposure
- Information Technology61.98%
- Financials21.09%
- Consumer Discretionary9.85%
- Communication Services3.87%
- Energy3.17%
- Health Care0.04%
Weight Changes
Notable position adjustments in the latest snapshot.
Performance vs Benchmark
Strategy NAV vs benchmark — hover for exact values.
Alpha Trend
Excess return vs benchmark over time.
Drawdown Trend
Underwater curve and peak drawdown marker.
Turnover Trend
Per-period turnover with average reference.
Strategy Comparison
All four default strategies side-by-side.
| Strategy | Annualized | Alpha | Sharpe | Max DD |
|---|---|---|---|---|
| Baseline | 25.74% | 10.02% | 1.06 | -27.69% |
| Momentum Screen | -2.19% | -13.50% | 0.06 | -42.34% |
| Basic Value Screen | 11.08% | -0.41% | 0.48 | -48.85% |
| Combo Equal Screen | 17.00% | 3.56% | 0.70 | -34.61% |
Recent Periods
Per-period performance vs benchmark.
| Period | Strategy | Benchmark | Excess | Turnover | Trades |
|---|---|---|---|---|---|
| 2022-12-31 | 10.56% | -0.25% | +10.81 | 2.60 | 6 |
| 2023-03-31 | 4.56% | 7.90% | -3.34 | 8.25 | 7 |
| 2023-06-30 | 1.85% | -1.77% | +3.61 | 4.38 | 7 |
| 2023-09-30 | 0.67% | 10.11% | -9.44 | 4.08 | 8 |
| 2023-12-31 | 2.92% | 4.96% | -2.04 | 7.13 | 8 |
| 2024-03-31 | 13.04% | 2.31% | +10.72 | 1.85 | 8 |
| 2024-06-30 | 2.94% | 9.83% | -6.89 | 3.32 | 8 |
| 2024-09-30 | 5.91% | 2.76% | +3.15 | 9.94 | 8 |
| 2024-12-31 | -9.52% | -3.63% | -5.89 | 8.91 | 7 |
| 2025-03-31 | 6.70% | 9.22% | -2.52 | 13.56 | 9 |
| 2025-06-30 | 13.73% | 4.20% | +9.53 | 7.29 | 9 |
| 2025-09-30 | -0.28% | 1.49% | -1.77 | 9.90 | 8 |
Strategy Q&A
Pre-generated questions and answers about this strategy.
- baseline13FChat AI
What does directly following the disclosed baseline portfolio expose an investor to?
Directly following the baseline exposes an investor to very high concentration in a few large-cap names, especially Apple. In the baseline artifact, AAPL is 51.42%, BRK.A 21.09%, and NVDA 7.89%, while the top 5 total 91.45% and the top 10 99.84%. Sector exposure is similarly concentrated: Information Technology is 61.98% and Financials 21.09%. That structure helped drive a 25.74% annualized return and 10.02 alpha, but it also means portfolio risk is dominated by a handful of securities rather than diversified factor or sector bets.
strategyViews.baseline.topHoldingsstrategyViews.baseline.concentrationstrategyViews.baseline.sectorWeightsstrategyViews.baseline.metricsstrategyViews.baseline.weaknesses↳ Show me how much of baseline return and drawdown came from AAPL, BRK.A, and NVDA concentration.
- baseline13FChat AI
Which recent baseline periods best explain the risk-return trade-off?
The baseline trade-off is well illustrated by a mix of strong alpha periods and weak, concentrated drawdown periods. Positive examples include 2024-03-31, when optimized return was 13.04% versus SPY at 2.31% for +10.72% excess, and 2025-06-30, when return was 13.73% versus 4.2% for +9.53% excess. Weak examples include 2024-06-30, when baseline returned 2.94% versus SPY at 9.83% for -6.89% excess, and 2024-12-31, when baseline lost -9.52% versus SPY at -3.63% for -5.89% excess. So the same concentrated structure that generated outsized upside also created periods of meaningful benchmark lag and a -27.69% max drawdown.
strategyViews.baseline.periodPerformancestrategyViews.baseline.metrics.maxDrawdownstrategyViews.baseline.metrics.annualizedReturn↳ Plot the best and worst baseline periods against turnover and concentration to see when concentration paid off.
- baseline13FChat AI
What should a user inspect next before deciding whether the baseline is acceptable?
A user should inspect three things next: single-name concentration, turnover spikes, and lag risk. The baseline artifact flags Apple above 51% weight, top five above 91%, and a period with 98.9% rebalance turnover in the risk notes. It also notes filing-based implementation delay, which is critical for a 13F strategy because actual trades can occur weeks after the manager acted. Even though estimated implementation cost was only 1.3837 and Sharpe was 1.06, the combination of concentration and lag can make realized results diverge sharply from the backtest.
strategyViews.baseline.riskNotesstrategyViews.baseline.metrics.totalEstimatedCoststrategyViews.baseline.metrics.sharpestrategyViews.baseline.concentration↳ Can you summarize baseline acceptability as a checklist using concentration, turnover, cost, and 13F lag?
該基金的其它策略
動量篩選
Select holdings by historically observable momentum, targeting roughly one quarter of each period's original member count and no more than 20 names; when a period has over 100 members, pre-rank to the top 50 first.
價值篩選
Select holdings using PE, PB, P/FCF, and EV/EBITDA, targeting roughly one quarter of each period's original member count and no more than 20 names; when a period has over 100 members, pre-rank to the top 50 first.
綜合等權
Filter for large-cap, quality, and low-leverage holdings, rank by composite quality/value/size score, keep the top 20 names, and equal-weight the selected names.