MVAL.X — Meridian Fund, Inc. - Meridian Contrarian Fund 13F holdings and portfolio analysis

已就緒Meridian Fund, Inc. - Meridian Contrarian Fund · James England

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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 diversified but still idiosyncratic stock-picking portfolio with delayed 13F-style implementation and moderate trading friction. Structurally, concentration is not extreme—top5 is 16.72%, top10 is 29.95%, and top20 is 51.84%, with the largest holding FCNC.A only 4.04%. But the actual exposures are active and eclectic: Industrials are 22.84%, Information Technology 21.11%, Financials 15.35%, and Health Care 11.38%, with named positions such as FCNC.A, DLTR, TCBI, LASR, and NVST leading the book. The risk side is that this baseline still produced only 6.27% annualized return, a negative information ratio versus SPY, 869 trades, and 1.1979 total estimated cost under delayed filing execution.

↳Show me how much of the baseline risk comes from the top 10 names versus sector tilts and delayed filing implementation.
baseline13FChat AI
Which recent baseline periods best explain the risk-return trade-off?

The recent baseline periods that best explain the trade-off are 2024-06-30, 2024-12-31, and 2025-03-31. In 2024-06-30 the portfolio returned 1.50% versus 9.83% for SPY, an -8.33% excess return despite 10.48 turnover and 16 trades, which captures the opportunity cost of the lower-beta style in a strong market. In 2024-12-31 it returned 0.14% while SPY lost -3.63%, producing +3.76% excess with only 4.37 turnover and 12 trades, which shows the defensive side of the strategy. Then in 2025-03-31 it gained 1.85% versus SPY’s 9.22%, a -7.37% excess return with 8.03 turnover and 14 trades, reinforcing that the portfolio can hold up better in risk terms but often lags in strong benchmark rallies.

↳Plot the baseline period excess returns against turnover so I can see when trading helped and when the low-beta style simply lagged SPY.
baseline13FChat AI
What should a user inspect next before deciding whether the baseline is acceptable?

A user should inspect three things next: hidden concentration by sector, implementation drag, and the actual sources of underperformance versus SPY. First, the baseline’s visible sector mix is active—Industrials 22.84%, Information Technology 21.11%, Financials 15.35%, and Health Care 11.38%—so you need to decide whether those sector bets fit your market view. Second, the backtest incurred 869 trades and 1.1979 totalEstimatedCost, and the risk notes say delayed filing implementation and slippage were material. Third, the weaknesses and attribution data show the biggest drags came from Energy (-10.43 sector attribution), Health Care (-9.60), Consumer Staples (-9.16), Utilities (-7.77), and Materials (-7.75), so it is important to verify whether those are temporary misses or persistent style headwinds.

↳Decompose the baseline’s relative underperformance into sector attribution, stock selection, and trading-cost drag before I decide if it matches my risk tolerance.
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