Using 13F Filings for Sector Rotation: Reading the Money Flow Between Industries

Why rotate the analysis up a level

A single fund adding a single stock is noise: it may be a hedge, a flow trade, or a client mandate. But when the aggregate share-count change of hundreds of managers in one industry moves by hundreds of billions, that is a regime expression — too large and too broad to be idiosyncratic. Sector rotation from 13F data is the practice of reading those aggregate flows, quarter over quarter.

The method on this site

For the latest filing quarter, we sum each position's share change versus the prior quarter and value it at the current quarter-end close, then group by industry. Positions without price data are excluded, broad ETFs are filtered out, and exited positions count as sells (their previous shares had no buyer). The full table lives on the sector money flow ranking and the heatmap on the sector flow visual.

What 2026-Q2 actually shows

The quarter's rotation was unusually lopsided. Consumer Discretionary took in +$399.9B — the largest inflow by far, with 14,265 adds against 9,601 cuts. Industrials (+$129.6B), Health Care (+$106.4B) and Financials (+$94.2B) follow. The exit door was almost exclusively one sector: Technology saw -$1,037B of net share cuts — institutional selling of the entire AI/semiconductor complex, every other sector's flow rounding to noise beside it.

Four traps in flow-based rotation

• Passive giants distort everything. Index managers' “sells” of Technology mirror fund outflows, not a view — filter to active managers before reading a flow as conviction.
• Price effects leak into the valuation. Shares valued at the current quarter-end close mean a crashed sector's cuts look smaller and a rallied sector's adds look bigger.
• The 45-day delay is a headwind. You are reading a position that is at least one quarter plus 45 days old — rotation may already have reversed.
• Sector labels are messy at the edges. Source data mixes e.g. “Technology” and “Information Technology”; treat sector boundaries as approximate.

Turning flows into a watchlist

A workable loop: pick the top-2 inflow sectors, then use the stock consensus ranking and biggest position increases restricted to those sectors to find the specific names institutions rotated into; cross-check with value inflow to confirm dollar backing. Sector flow tells you where to fish; stock-level rankings tell you what the fish looks like.