Mag7 Churn: The Same Names Funds Are Adding and Cutting
This is an AI analysis of an interesting pattern in QuantyFight data derived from SEC 13F holdings: AMZN, MSFT, NVDA, META, GOOGL, and AAPL simultaneously top managers-increasing and managers-decreasing / exiting leaderboards — a two-way ownership pattern rather than a one-direction pile-in.
Last reviewed: 2026-09-24Filing window: Q1 2026 vs Q4 2025Source: QuantyFight · SEC 13F-derived data
How to read this article. This is AI analysis of interesting patterns in QuantyFight data derived from SEC 13F holdings. Numbers, ranks, share counts, and sector labels come from QuantyFight’s 13F-derived data whose ultimate source is the SEC Form 13F data sets archive. Primary Q1 2026 filing accession: 0001193125-26-226661. The connecting narrative is AI-assisted interpretation for readability — not investment advice.
The Q1 2026 Mag7 churn table
Manager-count KPIs on QuantyFight (hedge-flagged leaderboard) for the latest filing window:
High counts on both sides usually mean the name is widely held and actively rebalanced — not that “everyone is selling” or “everyone is buying.” AAPL’s 122 decreasing vs 68 increasing managers is a useful caution against reading Mag7 as a single directional consensus.
Counts are not dollar-weighted. One Berkshire-sized GOOGL add can outweigh dozens of small decreases in dollar terms — which is why QuantyFight pairs manager-count KPIs with dollar-mover leaderboards.
Dollar leaders vs count leaders
Contrast: Mag7 count leaders vs selected $ prints
Signal
Example on QuantyFight
Count breadth
AMZN 140 managers increasing (top of increasing KPI)
Data caveats (important). Form 13F snapshots are delayed, cover reportable U.S. long securities for managers over the SEC threshold, and exclude shorts, many derivatives, cash, and non-13(f) exposures.
“AUM” / book figures on QuantyFight refer to disclosed long value derived from SEC 13F holdings, not a manager’s full firm AUM.
Large share changes can reflect sales, transfers, share-class mechanics, or reporting transitions — treat movement rows as research starting points.
This article is AI analysis for information only and is not investment advice.