Reading sector rotation: what the 11 Sector ETFs tell you

An index is a single number, but the 11 sectors beneath it often move in wildly different directions. Understanding sector rotation gives you a more three-dimensional read on “what the market is thinking today.”

Why the 11 Select Sector SPDRs

The most common U.S. sector scheme is State Street's Select Sector SPDR family, which splits the S&P 500 into 11 sectors, each with a matching ETF:

• Information Technology XLK, Communication Services XLC, Consumer Discretionary XLY, Financials XLF, Health Care XLV, Industrials XLI, Consumer Staples XLP, Energy XLE, Utilities XLU, Real Estate XLRE, Materials XLB

Each ETF's holdings and weights are public, so we can use the same logic as single-stock contribution to compute a constituent's percentage-point contribution to its sector ETF:

contribution_% ≈ w_in_etf_i × r_i

w_in_etf_i is the constituent's weight within the ETF, and r_i is its move for the day. Sort constituents high to low and you can see “who is driving this sector.”

“Cyclical” and “defensive” sectors

Markets often split sectors into two rough groups — this is a general, textbook classification, not a trade recommendation:

• More cyclical: technology, consumer discretionary, industrials, financials, materials. Typically more active when the economy looks optimistic.
• More defensive: consumer staples, utilities, health care. Money often rotates here when markets turn cautious.

When you see “defensive sectors relatively strong today, cyclicals lagging,” that often reflects the market's current risk appetite. But note: single-day sector performance is very noisy — one day's rotation is not a trend, and should be viewed over a longer window.

How we present it

On the Market Data page you'll see:

1. The 11 Sector ETFs ranked for the day — strongest to weakest, so you can see at a glance who led and who lagged.
2. A sector heatmap — tile area is weight, color is the move, so you can quickly scan where money is concentrated.

All numbers are computed by code with an open method. We present an angle of observation, not an instruction on “which sector to buy.”

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Further reading: Reading “index point contribution”.