Every quarter when a publicly traded company releases earnings, the stock experiences an immediate repricing event. This tool evaluates a security's historical earnings and converts it into structured statistical probabilities.
For any given equity ticker, the framework analyzes:
Gap Distribution: The historical frequency and average Gap Ups and Gap Downs. (For example, AAPL gapped up following 49 of its past 80 earnings reports and gapped down 31 times, averaging +4.24% and −4.29% respectively).
Gap-Day Intraday Drift: Performance during the first tradeable session measured strictly Open-to-Close (O→C).
Multi-Time Frame Forward Drift: Forward performance at 5-Day, 10-Day, 30-Day, and Until Next Earnings intervals, all measured from the post-earnings opening price.
AAPL closed at $271.35 before the report and opened at $278.86 the next morning, a +2.77% earnings gap. The reaction session then drifted open to close by about −0.85%. The shaded band is price nobody traded while the market was shut.
Isolating the Overnight Gap vs. Intraday Session
The Earnings Gap: The percentage difference between the last pre-earnings closing price and the first post-earnings opening price. This represents overnight repricing during market closure, a move individual retail traders cannot execute during regular hours.
The Gap Day (O→C): The price movement from the post-earnings Open to the post-earnings Close. This isolates actionable market behavior: what institutions and retail traders executed once trading opened.
Gap Day Drift (%) = (ClosePost − OpenPost) ÷ OpenPost × 100
Why the Separation Matters
A stock can gap UP +5.0% overnight on news, but then sell off −3.0% during the regular trading session. A traditional Close-to-Close metric (+1.85%) hides both the gap and the intraday weakness. Splitting the metrics exposes real edge.
Companies report earnings at different times of day. Misaligning the reporting timestamp invalidates post-earnings statistical calculations.
Reporting Windows & Reaction Mapping
Report Timing
Catalyst Context
Correct Reaction Session
Before Open (BMO)
Released before 9:30 AM ET market open.
Same Calendar Day (Session 0)
After Close (AMC)
Released after 4:00 PM ET market close.
Next Trading Day (Session +1)
Report
What Follows
Reaction Session
BMO Report @ 8:00 AM
Market Opens @ 9:30 AM
Day 0
AMC Report @ 4:15 PM
Overnight Interbank
Day +1
Operational Significance
Major financial institutions and large-cap industrial firms frequently report Before Market Open (BMO). Properly identifying the timing prevents shifting or corrupting data across decades of reports.
Chapter 3
Summary Metrics & Behavioral Patterns
The summary dashboard aggregates historical performance across all recorded quarters (e.g., 80 historical quarters for AAPL).
Empirical Performance Summary (AAPL Benchmark)
AAPL Historical Overview (80 Quarters)
Gap Up Frequency
61.3% (49 quarters) · Average Up Gap +4.24%
Gap Down Frequency
38.7% (31 quarters) · Average Down Gap −4.29%
Max Gap Up Record
+9.88% (April 2012)
Max Gap Down
−12.37% (Jan 2008)
Post-Gap Behavioral Patterns
Analyzing post-earnings performance across 80 quarters reveals differences between short-term intraday behavior and multi-month post-earnings drift (PEAD):
Scenario
Gap Day O→C Green (%)
Gap Day Avg Return
Green % by Next Earnings
Avg Return by Next Earnings
After Gap Up
39.0%
−0.48%
65.0%
+7.24%
After Gap Down
55.0%
+0.34%
68.0%
+3.39%
Intraday Fade vs. Long-Term Drift
On Gap Day (Day 0), AAPL exhibits profit-taking: up gaps fade (−0.48%), down gaps experience mild bounce (+0.34%). By Next Earnings (~60 days), secular momentum dominates: 65% to 68% of quarters resolve positive regardless of gap direction.
Chapter 4
Setting the Gap Threshold
The Gap Threshold is an interactive filter that segregates historical earnings reports into Large Gaps versus Small Gaps.
By default, the threshold seeds itself to the percentage size of the stock's most recent quarterly gap (e.g., +2.77%).
Step
Result
All Historical Gaps (80 Quarters)
Starting sample
Filter: Gap Size ≥ 2.77%
Large Gap Sample (32 Up / 20 Down Quarters)
Large Gap Drift Comparison (AAPL: All vs. ≥ 2.77% Threshold)
Sample Group
Gap Day Green (%)
10-Day Win Rate (%)
10-Day Avg Return
Next Earnings Win Rate
Next Earnings Avg Return
All Gap Ups
39.0%
59.0%
+1.40%
65.0%
+7.24%
Gap Ups ≥ 2.77%
34.0%
66.0%
+1.76%
75.0%
+9.96%
Key Finding on Threshold Intensity
As gap size increases, intraday profit-taking intensifies (Gap Day green rate drops from 39% to 34%). However, institutional buying power over multi-week time frames strengthens significantly (Next Earnings win rate climbs to 75%).
The Historical Log provides granular, row-by-row visibility into every quarterly earnings report on record.
Report Date
Earnings Gap
Gap Day (O→C)
5 Days
10 Days
20 Days
Until Next Report
Apr 30, 2026
+2.77%
−0.85%
+1.20%
+2.10%
+4.50%
+8.30%
Jan 29, 2026
−1.45%
+0.30%
−0.50%
+0.80%
+1.10%
+3.20%
Oct 30, 2025
+4.10%
−1.20%
+2.40%
+3.15%
+6.80%
+11.40%
Historical Log (AAPL sample data)
Sorting Strategies for Statistical Analysis
Sorting by Earnings Gap: Brings the largest historical catalysts to the top. Allows traders to visually inspect whether extreme gaps result in immediate reversals or sustained trend continuation.
Sorting by Until Next Earnings: Highlights macro-winner quarters regardless of whether the initial overnight gap was positive or negative.
Execution Takeaway
Every metric across a single row originates from the exact same post-earnings opening price. This provides a clear historical view of the full quarterly lifecycle following an earnings announcement.