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DaddyElonMusk69
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earnings-forecast

Generate trading signals from earnings surprises and analyst consensus deviations.

Updated Apr 12, 2026
Search Tags:#forecasting#earnings#consensus-estimates#pead#sue#analyst-momentum#event-driven-trading
One-click install
npx skills add https://github.com/DaddyElonMusk69/motis-agent --skill earnings-forecast-daddyelonmusk69
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: earnings-forecast
Source: https://github.com/DaddyElonMusk69/motis-agent/tree/main/skills/finance/earnings-forecast
Command: npx skills add https://github.com/DaddyElonMusk69/motis-agent --skill earnings-forecast-daddyelonmusk69

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

The skill identifies earnings surprises and consensus deviations to convert analyst forecast differences into actionable short- to medium-term trading signals, reducing manual research and improving event-driven trade timing.

Core Features & Use Cases

  • Earnings surprise standardization (SUE): Compute standardized unexpected earnings to quantify the magnitude of EPS beats or misses relative to historical forecast errors.
  • PEAD execution windows: Turn SUE signals into timed PEAD trades with configurable holding periods and universe constraints for A-share markets.
  • Analyst revision momentum (ERM & dispersion): Track up/down analyst revisions, consensus drift, and dispersion to filter and prioritize signals.
  • Use case: Run a bottom-up EPS forecast for a large-cap consumer stock, compare to Wind/東財 consensus, calculate SUE and ERM, and produce a buy signal to hold through a 40-day PEAD window.

Quick Start

Run an earnings surprise analysis for a target stock by comparing your EPS forecast to the latest analyst consensus, calculate SUE and ERM, and return a buy/hold/sell signal with a suggested holding period.

Frequently Asked Questions about earnings-forecast

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

FAQPage Schema
How do I calculate standardized unexpected earnings to generate trade signals?▼

Earnings surprises are quantified using standardized unexpected earnings by comparing your EPS forecast to analyst consensus and historical forecast errors, generating actionable buy, hold, or sell trading signals based on the deviation magnitude.

What is PEAD and how does it work for event-driven trading?▼

PEAD, or post-earnings-announcement drift, applies SUE signals to timed trades with configurable holding periods and universe constraints, allowing A-share event-driven strategies to capitalize on sustained price momentum following earnings announcements.

Can I use analyst revision momentum to filter earnings surprise signals?▼

Analyst revision momentum filters and prioritizes earnings surprise signals by tracking up and down analyst revisions, consensus drift, and dispersion metrics alongside SUE calculations to validate the strength of the trading signal.

What data do I need to compute SUE and ERM for A-share earnings forecasting?▼

Computing SUE and ERM requires historical quarterly EPS, analyst consensus time series, announcement dates, rolling standard deviation for forecast errors, dispersion metrics, and portfolio rebalancing rules to execute A-share event-driven strategies.

How do I run an earnings surprise analysis for a specific stock?▼

Run a bottom-up EPS forecast for a target stock, compare it to the latest analyst consensus, calculate SUE and ERM, and return a buy, hold, or sell signal with a suggested PEAD holding period for event-driven trade timing.

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