Post-Earnings Drift Pattern

Overview

This pillar analyzes the Post-Earnings Announcement Drift (PEAD), a market anomaly where a stock's price continues to trend in the direction of an earnings surprise. It identifies historical patterns to forecast medium-term price action after an earnings report.

What It Does

The pillar quantifies a company's historical tendency to drift upwards after positive earnings surprises and downwards after negative ones. It analyzes the magnitude of past surprises against the subsequent 60-day stock performance. This process creates a predictive model for the likely direction and strength of the post-announcement trend.

Why It Matters

Markets are often slow to fully incorporate the implications of an earnings report, creating a predictable inefficiency. This pillar exploits that underreaction, providing a statistical edge for forecasting price movements beyond the initial one-day reaction that most traders focus on.

How It Works

First, the pillar gathers historical earnings data, including consensus estimates and actual reported figures, to calculate the 'surprise' factor. It then tracks the stock's cumulative return in the 60 trading days following each past announcement. By correlating the surprise magnitude with the drift performance, it generates a signal about the expected price trend for the upcoming post-earnings period.

Methodology

The core calculation is the Historical PEAD Factor, derived by comparing the average cumulative abnormal returns (CAR) for stocks in the top quartile of earnings surprises against those in the bottom quartile over a 60-day window. The analysis uses a 5-year lookback period for historical data. Surprise is defined as (Actual EPS - Median Consensus EPS) / Stock Price.

Edge & Advantage

This provides a data-driven edge by focusing on a well-documented market inefficiency, allowing for predictions on medium-term trends that short-term news cycles often obscure.

Key Indicators

• Historical PEAD Factor

  high

  Measures the historical strength and consistency of the stock's price drift following earnings surprises.

• Surprise Magnitude

  high

  The percentage by which the reported earnings per share (EPS) beat or missed consensus estimates.

• Implied vs Realized Volatility

  medium

  Compares the options market's expected move to the actual price move post-earnings, indicating how well the market prices the event.

Data Sources

• FactSet / Refinitiv

  Provides consensus and actual corporate earnings data.

• Polygon.io

  Source for historical daily stock price and volume data.

• CBOE

  Provides historical options data to calculate implied volatility.

Example Questions This Pillar Answers

• → Will Apple (AAPL) stock close higher 30 days after its next earnings report than it did on the report day?
• → Will Tesla (TSLA) outperform the QQQ ETF in the 60 days following its Q3 earnings announcement?
• → What will be the price range of NVIDIA (NVDA) stock in the month after its upcoming earnings call?

Tags