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INFLATION RESEARCHSTUDY PROTOCOL / VERSION 0.1AUGUST 2026
RESEARCH IN PROGRESS

CPI RELEASE
IMPACT ON
S&P 500 RETURNS

An event-study framework for measuring how equity returns respond to U.S. inflation surprises across multiple horizons and volatility regimes.

AUTHORJordan JohnsonFIELDMacroeconomics × Quantitative Finance
80+PLANNED RELEASE
OBSERVATIONS
03PRIMARY RETURN
WINDOWS
05CORE DATA
SERIES
v0.1CURRENT
PROTOCOL

Scheduled inflation releases concentrate new information into a known moment. That makes CPI announcements a useful laboratory for studying how markets process macroeconomic surprises.

This study is designed to estimate the direction, magnitude, and persistence of S&P 500 reactions following U.S. Consumer Price Index releases. It separates the announced inflation level from the surprise relative to expectations and conditions the response on the pre-release volatility regime.

The artifact presented here is a preregistration-style research protocol. It defines the question, variables, event windows, tests, and limitations before the final dataset is analyzed. Results will be added only after data validation and reproducible code review.

WHY PUBLISH THE PROTOCOL?To make the hypothesis testable before the result is known and reduce the temptation to redesign the question around a preferred outcome.
How do the size and direction of CPI surprises affect S&P 500 returns over one-, five-, and ten-trading-day windows—and does the pre-release volatility regime change that response?
INFORMATIONActual CPI − consensus CPI

Measures what the market learned, not simply the reported inflation rate.

CONDITIONPre-release VIX regime

Tests whether uncertainty amplifies or dampens the price response.

RESPONSEForward S&P 500 return

Tracks immediate reaction and short-horizon persistence.

H1

NEGATIVE SURPRISE RESPONSE

Higher-than-expected inflation is associated with lower same-day S&P 500 returns, on average.

DIRECTIONAL / PRIMARY
H2

VOLATILITY AMPLIFICATION

The absolute return response is larger when pre-release implied volatility is elevated.

CONDITIONAL / PRIMARY
H3

RESPONSE DECAY

The relationship weakens across the five- and ten-day windows as other information enters prices.

HORIZON / SECONDARY
H4

ASYMMETRIC REACTION

Upside inflation surprises create a different magnitude of response than equally sized downside surprises.

NONLINEAR / EXPLORATORY

EVENT STUDY,
WITH THE ASSUMPTIONS
LEFT VISIBLE.

01 / SAMPLE

Release selection

Monthly U.S. CPI releases over an approximately 80-event history. Each event receives a timestamp, release date, actual value, expected value, and prior value.

02 / SURPRISE

Standardized signal

The raw surprise is actual minus consensus. A standardized version divides by the rolling dispersion of past surprises to improve comparability through time.

03 / RETURNS

Response windows

Calculate close-to-close and, where the timestamp permits, open-to-close S&P 500 returns for 1D, 5D, and 10D forward windows.

04 / REGIMES

Volatility condition

Classify events using the distribution of pre-release VIX levels. Sensitivity analysis will compare binary and quantile-based regime definitions.

05 / ESTIMATION

Model family

Begin with difference-in-means and nonparametric tests, then estimate regression specifications with interaction terms and robust standard errors.

06 / VALIDATION

Robustness

Test alternate event windows, winsorization rules, surprise definitions, and influential observations. Report sensitivity rather than selecting one convenient specification.

BASE SPECIFICATIONRt→t+k = α + β₁·Surpriset + β₂·HighVIXt + β₃·(Surprise × HighVIX)t + εt

Where k ∈ {1, 5, 10} trading days. Coefficient β₃ tests whether volatility regime changes the relationship between the inflation surprise and subsequent return.

SERIESVARIABLEROLESOURCE PLAN
01Headline CPIYoY / MoMEvent informationBLS / FRED
02Core CPIYoY / MoMPersistence measureBLS / FRED
03ConsensusExpected CPISurprise baselineEconomic calendar archive
04S&P 500OHLC / adjusted closeReturn responseMarket data provider
05VIXClose / pre-release levelVolatility regimeCBOE / FRED
062Y TreasuryYield changeRate-path controlU.S. Treasury / FRED

SOURCE GOVERNANCE / Final paper will record download dates, transformation logic, missing-value decisions, revisions, and a machine-readable data dictionary.

FROM RAW RELEASE
TO DEFENSIBLE CLAIM.

PIPELINE / 01—06
01

INGEST

Collect releases and market series

02

VALIDATE

Audit dates, timestamps, and missingness

03

ENGINEER

Create surprises, regimes, and returns

04

DESCRIBE

Inspect distributions and influential events

05

ESTIMATE

Run primary and sensitivity specifications

06

REPORT

Publish results, code, and limitations

NEGATIVE RESPONSEZEROPOSITIVE RESPONSE
1-DAY5-DAY10-DAY

ILLUSTRATIVE OUTPUT DESIGN / Points and intervals above are placeholders showing the planned reporting format. They are not empirical estimates.

01

SMALL EVENT SAMPLE

Monthly releases provide relatively few observations, limiting power and the complexity of defensible models.

02

OVERLAPPING INFORMATION

Other macro news, earnings, geopolitical events, and policy communication can affect returns within the same window.

03

CHANGING REGIMES

The meaning of an inflation surprise depends on the policy and growth environment; a stable full-sample coefficient may hide structural change.

04

CONSENSUS QUALITY

Historical expectation data may vary by provider and snapshot timing, making provenance essential.

THE NEXT QUESTION
IS PART OF THE RESULT.

  1. 01Compare equity response with Treasury yields, sector ETFs, and style factors.
  2. 02Model the full intraday response when high-frequency data becomes available.
  3. 03Test whether text from CPI releases adds information beyond the headline surprise.
  4. 04Compare CPI reactions across monetary-policy regimes and inflation eras.

U.S. Bureau of Labor Statistics. Consumer Price Index release documentation and historical tables.

Federal Reserve Bank of St. Louis. FRED economic data series and metadata.

Cboe Global Markets. VIX methodology and historical index data documentation.

MacKinlay, A. C. Event studies in economics and finance. Journal of Economic Literature.

Campbell, Lo & MacKinlay. The Econometrics of Financial Markets.

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RESEARCH PROTOCOL / v0.1

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