Did the June 2026 Fed hawkish pivot actually move Tech?

Validation case — reproduces the original finding from ../causal/run_causal_report.py. Confirms the generalized toolkit recovers the same (honest, negative) result: XLK's gap vs. its synthetic counterfactual opened up months before the June 17 FOMC meeting, so the pivot itself can't cleanly take credit for it.

Actual vs. synthetic counterfactual

7198126154181 Treatment date Actual Synthetic
Actual Synthetic (counterfactual)

Fit quality

Fit-window RMSE7.8683
RMSE ÷ fit-window std dev0.60×
Fit-window days417
Confound-window mean gap+13.17
Post-period mean gap+35.54

Placebo test — same method run on every unit, treated one highlighted

UnitMean post-period gapMax abs. gap
XLK (treated)+22.28%31.16%
XLI+13.10%17.25%
XLC-8.39%12.41%
XLF+7.34%13.70%
XLY-7.03%13.90%
XLP-5.41%7.02%
XLV-3.96%11.72%
XLB-2.73%7.00%
XLE+2.25%13.24%
XLRE+1.41%3.09%
XLU-1.31%3.85%

Verdict

Caution on fit quality: the fit-window RMSE is 0.60× this unit's own fit-window standard deviation — a loose fit. Treat the gap below as suggestive at best, not a clean read.

XLK's post-period gap ranks #1 of 11 units by absolute size in the placebo test (larger rank = more likely a real, unit-specific effect rather than noise the method would produce for any random unit).

Caution: the confound-window gap (+13.17) is already a substantial fraction of the post-period gap (+35.54) — this divergence looks like it was emerging before the treatment date, so the treatment can't cleanly take full credit for the post-period gap.

Read: this looks like a real, unit-specific effect — the gap this method finds for the treated unit is larger than what it produces when re-run on most other units in the donor pool.