Central Banks & Macro risk-off · 0–6 months
A what‑if from the future

What if the Bank of England cuts rates into sticky inflation?

A BOE cut as services inflation reignites is a credibility error: sterling and gilts sell on a fiscal-dominance read even as the front end prices easing — the curve bear-steepens, the opposite of a clean risk-on. Rhymes with the September 2022 mini-budget gilt crisis, where loss of fiscal/monetary credibility crushed GBP and long gilts together. Forward: stickier UK services CPI makes the credibility hit faster than a textbook dovish cut.

20%
our model probability
over 0–6 months
prediction markets — the market's odds
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Anchored to measured history 20% · 90% range 9–31% · 40 dated precedents behind it — a wider range means thinner evidence

Every number ships with its receipt — the odds, the range, the precedents, and a public grade at Reality Check. The statistical machinery that produces it is proprietary.

The butterfly cascade

How this trigger trickles across markets, left → right — the root shock, its first‑order moves, then the ripple effects. Drag any node; tap a market for its real price history.

Resolution timeline — how this probability is moving

Our model's odds (electric blue) over time vs the market's (Polymarket, amber), from the past toward the 0–6 months horizon. Each dot is a real macro event that nudged the probability — green pushed it up, red pushed it down. Tap a dot for the source. Loading the probability audit trail…

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What it would mean

If this plays out, it is a risk-off shock. The Bank of England eases prematurely as services inflation reignites, sending sterling and gilts into a credibility-driven tailspin. The trigger decomposes into signed root‑shocks — Inflation surprise ▲ · Credit spreads ▲ · Real yields ▲ — which propagate through our causal graph to the markets below.

Methodology. Probability and impact are anchored to history and scored against what actually happens — wins and losses, in public, at Reality Check. Market odds live from Polymarket & Kalshi. By Vikas Singh, Quantitative Strategist. Updated 2026-08-13.