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XLK · Return Distribution

XLK · Return Distribution — Twenty-Seven Years of Technology Sector Returns

Tech Sector Return Distribution — Histogram of annual total returns for the technology sector, highlighting structural growth and recovery elasticity.

The plate

XLK · Return Distribution — Twenty-Seven Years of Technology Sector Returns0246-40%-20%0%20%40%60%
Plate IV.3 While long-term average returns rival semiconductors, overall dispersion is dampened by recurring software, SaaS, and IT services revenues that temper hardware cyclicality. Data through 2026-09-28

Latest Snapshot

Average
+13.8%
Positive years
20
Negative years
7
Best year
1999 +65.2%
Worst year
2000 -41.9%
Observations
28
Sample
1999 – 2026

While long-term average returns rival semiconductors, overall dispersion is dampened by recurring software, SaaS, and IT services revenues that temper hardware cyclicality.

What this page answers

This static page is built to answer searches for XLK · Return Distribution. It summarizes the live dataset behind the Twenty-Seven Years of Technology Sector Returns panel and links to the full interactive chart.

While long-term average returns rival semiconductors, overall dispersion is dampened by recurring software, SaaS, and IT services revenues that temper hardware cyclicality. The data is refreshed by the History of Market pipeline and published as a stable JSON endpoint for research, citation, and AI-agent use.

View the interactive chart Download raw JSON

Data & Source

GET /api/xlk/annual-tr.json — Canonical dataset endpoint.

Exchange closing prices · Company filings · Robert Shiller · FRED · NBER.

FAQ

Where does this data come from?

History of Market combines public market and macro datasets — exchange closing prices, company filings, Robert Shiller, FRED, NBER, and the UBS Global Investment Returns Yearbook (Dimson–Marsh–Staunton). The exact endpoint for this panel is linked below.

How often is it updated?

Daily-tier datasets refresh after the U.S. market close, with a broader weekly refresh on Sunday. The timestamp shown on this page comes from the JSON payload.

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Yes, for research and education with attribution to History of Market. Upstream data sources retain their own terms.