Post-Earnings Drift (PEAD) Forecast

Overview

This pillar analyzes the Post-Earnings Announcement Drift (PEAD), a market anomaly where a stock's price continues to move in the direction of an earnings surprise for weeks. It quantifies the likely strength and duration of this momentum, offering a valuable edge for medium-term predictions.

What It Does

The model calculates the magnitude of a company's earnings surprise relative to analyst expectations and historical performance. It then analyzes post-announcement trading volume and changes in institutional ownership to gauge market conviction. By combining these factors, it generates a predictive score for continued price drift.

Why It Matters

Markets often underreact to earnings news, creating a predictable, extended price movement. This pillar systematically identifies these opportunities, providing a data-driven forecast for a stock's trajectory over the weeks following an earnings report, long after the initial volatility has subsided.

How It Works

First, the system computes the Standardized Unexpected Earnings (SUE) score by comparing actual earnings per share to the consensus estimate. Next, it measures trading volume persistence and tracks institutional buying or selling activity. These inputs are then weighted against the stock's historical drift patterns to produce a final drift forecast.

Methodology

The core calculation is the Standardized Unexpected Earnings (SUE) score: (Actual EPS - Consensus EPS) / Price-deflated Standard Deviation of Analyst Forecasts. The analysis window covers the 60 trading days following the earnings announcement. Volume is measured using a Volume Persistence Factor (VPF), which compares the 10-day moving average of post-announcement volume to the 30-day pre-announcement baseline. The final drift score is a weighted average of the SUE score, VPF, and quarterly institutional ownership changes.

Edge & Advantage

It transforms a well-documented academic anomaly into a systematic, actionable signal, capturing value from the market's slow absorption of new information.

Key Indicators

• Standardized Unexpected Earnings (SUE)

  high

  Measures the size of the earnings surprise, which is the primary catalyst for the drift.

• Volume Persistence Factor

  medium

  Tracks if post-announcement trading volume remains elevated, confirming market conviction behind the move.

• Institutional Ownership Delta

  high

  Detects if large, informed investors are buying or selling post-announcement, a strong confirming signal.

Data Sources

• Refinitiv / FactSet

  Provides consensus analyst estimates and reported corporate earnings data.

• SEC EDGAR Database

  Source for 13F filings, which detail quarterly institutional investment holdings.

• Polygon.io

  Provides historical stock price and volume data required for drift and volume analysis.

Example Questions This Pillar Answers

• → Will MSFT stock close at least 5% higher 60 days after its next earnings report, given a positive surprise?
• → Will the post-earnings drift for NFLX be positive or negative one month after its Q3 earnings call?
• → Will GOOGL outperform the S&P 500 in the quarter following its earnings announcement?

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