Knowledge base · Event playbook
Rates shock (2022)
Rates shock (2022)
Definition
In 2022 the Fed raised rates from ~0 to over 4% inside nine months against 40-year-high inflation; the S&P 500 fell ~25%, the Nasdaq ~35%, and — the episode’s defining fact — LONG TREASURIES FELL ~30% ALONGSIDE equities. The classic 60/40 portfolio had one of its worst years on record because its hedge asset failed by construction: in an inflation-driven tightening, the stock-bond correlation flips positive. This is the KB’s living exhibit for regime- conditional hedging.
How it works / structure
- The correlation flip (the load-bearing mechanics):
2000-2021’s negative stock-bond correlation reflected
growth-fear regimes (bad news → rate cuts → bonds rally);
2022’s driver was inflation — bad news for bonds WAS bad
news for equities (rates up hurt both) — the
Campbell-Pflueger-Viceira framework realized out of
sample (
regime-rate-environments). - The duration massacre: long-duration assets repriced
by discounting arithmetic — 20+ year Treasury funds −30%+,
unprofitable-growth equities −60/80% (
fa-dcf-valuationduration transmission: the longest cash flows fell hardest, mechanically); value-over-growth factor spreads hit records (strategy-factor-investingregime dependence). - The event cadence: CPI releases displaced FOMC as the
month’s largest event (
event-cpiregime-amplitude section documents it — multi-sigma index moves on print days); every asset traded off the inflation path. - Collateral episodes: the UK gilt/LDI spiral (September
— leveraged duration hedgers forced into selling by
margin calls on the asset they hedged with) and crypto’s
correlation-to-one with risk assets
(
ext-cryptoregime exhibit).
When it applies
Cited whenever bond-hedge assumptions are evaluated (the
hedge is regime-conditional — this is the out-of-sample
proof); for duration-decomposed equity risk; for
inflation-regime event weighting; for allocation stress
tests (port-allocation-frameworks — any framework whose
backtest window is 2000-2021 embeds the old correlation
regime silently).
Risk profile & failure modes
- The central lesson: the diversifying asset’s correlation is a REGIME OUTPUT, not a property — portfolios must state which regime their hedge assumes and monitor the driver (inflation vs growth dominance).
- Backtest-window capture: two decades of negative
correlation trained a generation of frameworks (risk
parity levered the assumption) —
bias-recencyat the allocation layer, realized. - Nowhere-to-hide arithmetic: when the discount rate is the shock, cash is the only short-duration asset — 2022’s best major allocation was the one no framework recommended.
- Misuse: declaring the negative-correlation era dead — the regime flipped WITH its driver; 2023-25 saw partial reversion as inflation fell; the lesson is conditionality, not a new constant.
Evidence & limits
The policy path and market returns are public record; Campbell-Pflueger-Viceira (2020) is the peer-reviewed regime framework the year validated. The gilt/LDI mechanics are Bank of England-documented. Attribution of equity declines between rates and earnings expectations retains the usual decomposition uncertainty.
Falsifiable-thesis examples
Illustrations only, not signals:
- “The 60-day stock-bond correlation stays positive while trailing CPI exceeds 4% (regime-driver thesis)” — falsified by the paired series.
- “This portfolio’s stress test includes a both-assets-down −20%/−15% year and survives its drawdown budget (2022-floor audit)” — falsified by the scenario computation.
Cross-references
- The framework it validated:
regime-rate-environments,macro-inflation-linkages - The transmission:
fa-dcf-valuation(duration),ext-bonds-rates,strategy-factor-investing - The allocation lesson:
port-allocation-frameworks,bias-recency - The event cadence:
event-cpi; the sequel:episode-banking-stress-2023
Sources
- Federal Reserve — FOMC statements and Summary of Economic Projections, 2022 tightening cycle
- Campbell, J., Pflueger, C. and Viceira, L. (2020), Macroeconomic Drivers of Bond and Stock Risks — Journal of Political Economy 128(8), 3148-3185
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