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earnings-forecast

Quantify earnings forecast deviations by comparing independent EPS projections to consensus.

Updated Apr 14, 2026
Search Tags:#consensus#financial-modeling#pead#sue#earnings-forecast#analyst-revisions#stock-trading
One-click install
npx skills add https://github.com/Liangwei-zhang/six-stock --skill earnings-forecast-liangwei-zhang
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: earnings-forecast
Source: https://github.com/Liangwei-zhang/six-stock/tree/main/Vibe-Trading/agent/src/skills/earnings-forecast
Command: npx skills add https://github.com/Liangwei-zhang/six-stock --skill earnings-forecast-liangwei-zhang

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

This skill helps traders and researchers quantify earnings forecast deviations by comparing independent EPS projections to market consensus, enabling data-driven trading decisions around earnings surprises.

Core Features & Use Cases

  • Top-Down and Bottom-Up forecasting chains translate macro, industry, and company drivers into EPS estimates.
  • Standardized signals using SUE, PEAD, and analyst revision momentum to identify mispricing opportunities across equities.
  • Use Case: apply the framework to representative stocks to illustrate how forecast mispricing informs buy/sell decisions and momentum trades.

Quick Start

Provide an earnings forecast analysis for a target stock and generate a SUE/PEAD-based trading signal.

Frequently Asked Questions about earnings-forecast

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I calculate earnings forecast deviations against market consensus?▼

You can quantify earnings forecast deviations by comparing independent EPS projections to consensus estimates, applying SUE and analyst revision momentum to identify mispricing opportunities across equities.

What is the best way to generate trading signals from SUE and PEAD metrics?▼

The best way to generate trading signals is calculating Standardized Unexpected Earnings (SUE) and Post-Earnings-Announcement Drift (PEAD) metrics, translating forecast mispricing into actionable buy or sell decisions.

How does top-down and bottom-up financial modeling translate macro drivers into EPS estimates?▼

Top-down and bottom-up forecasting chains translate macro, industry, and company-level drivers into EPS estimates, which are then compared to consensus to reveal forecast deviations.

Can I apply analyst revision momentum across a target universe of stocks?▼

Yes, you can apply analyst revision momentum, SUE, and PEAD frameworks across a target universe to generate standardized trading signals with holding-period metrics.

How do earnings forecasting models handle nonstandard events?▼

Earnings forecasting models handle nonstandard events gracefully during the signal generation process, ensuring SUE, ERM, and dispersion metrics remain robust for target equities.

What outputs do I get from an earnings surprise analysis framework?▼

An earnings surprise analysis framework provides outputs including SUE, analyst revision momentum (ERM), forecast dispersion, and holding-period metrics to inform momentum trades.

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