Does the pre-FOMC drift still work?

The published effect was strong in the 1994-2011 sample. Later research and desk experience suggest it weakened, moved, or became conditional after the paper drew attention to it. Treat it as context, not a standalone edge.

Why do markets sometimes rally on bad economic news?

Because prints are traded against expectations and policy implications rather than in isolation. Weak data can imply easier policy, which can lift risk assets. The sign of the reaction is regime-dependent, which is exactly what a playbook is for.

What is an economic surprise index?

A rolling aggregate of how releases compare with consensus forecasts; positive means data is beating expectations on balance. Methodologies are proprietary and differ by publisher, so use one series consistently.

Should I trade the release itself?

Liquidity is at its worst in the seconds around a top-tier print: spreads widen, depth vanishes, and slippage can be severe. Many funded-trader programs restrict trading around major releases. Most playbooks work the setup before and the resolution after, not the print.

Concept

Macro Event Playbooks

Macro Event Playbooks, also known as pre-FOMC drift, NFP/CPI, surprise indices, PMI/ISM cycles, are Breadth, Sentiment & External Data concepts. A reference entry: the Library explains it rather than implements it.

What are macro event playbooks?

Macro event playbooks are the prepared routines traders build around scheduled economic releases and central bank decisions: FOMC meetings, CPI, nonfarm payrolls, and the PMI/ISM survey cycle. They are not an indicator but a calendar discipline, knowing when liquidity thins, when volatility is priced to expand, and what the typical paths into and out of each event have looked like.

Parts of this are formally documented. The best-known example is the pre-FOMC announcement drift: New York Fed researchers Lucca and Moench found that, in their 1994-2011 sample, a disproportionate share of US equity returns accrued in the 24 hours before scheduled FOMC announcements. Follow-up work suggests the effect weakened or shifted after publication. Other pieces are structural rather than statistical: options markets mark up implied volatility into CPI and FOMC and reset it afterward, and spreads typically widen in the minutes around a print.

Playbooks also lean on aggregators. Economic surprise indices track whether data is beating or missing consensus in aggregate (Citigroup's is the most cited), and ISM/PMI readings above or below 50 frame where the growth cycle sits when a new print lands.

Why there's no indicator for this

None of this is computable from candles. The raw materials are an economic calendar with exact release timestamps, consensus forecasts, actual prints, and revisions, licensed from providers such as Bloomberg, Refinitiv, or Econoday, plus central bank schedules and, for surprise indices, proprietary weighting methodologies owned by their publishers. A chart script cannot know that CPI came in a tenth hot or what consensus was, and even backtesting event behavior requires point-in-time consensus history that price and volume cannot reconstruct.

There is a second honesty problem: most event effects are averages over long samples with wide dispersion, not per-event edges. Hard-coding a drift or a reversal pattern into a signal manufactures overfitting on top of missing data, which is why this stays a playbook rather than an indicator.

How traders use it

Risk scheduling: cutting size, widening stops, or going flat into CPI, FOMC, and payrolls, then re-engaging once the initial spike-and-reversal sequence resolves; many funded-trader programs mandate versions of this.
Volatility positioning: comparing the event premium priced into options against typical outcomes, trading the post-event volatility reset, and watching the VIX term structure kink around FOMC dates.
Scenario grids: writing the reaction map in advance, for example a hot CPI implying yields up, dollar up, long-duration equities down, with invalidation levels, then trading the confirmed reaction using intermarket analysis and DXY correlation regimes.
Regime weighting: surprise-index trends and the ISM cycle set how much a single print matters; the same payrolls number reads differently in an accelerating economy than in a slowing one.
Post-event structure: expecting whipsaws in the first minutes and using gamma exposure context to judge whether the market is likely to pin or accelerate once the print is absorbed.

Concept family

Breadth, Sentiment & External Data

63 concepts mapped · 63 in the Library