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Earnings Forecast & Consensus Gap

Builds EPS forecasts and flags earnings-surprise trading signals versus analyst consensus (A-shares focus).

Source Download skill
Repository
HKUDS/Vibe-Trading
Stars
37,433
Licence
MIT
Files
1 file

What it does

This skill teaches an AI agent a structured method for analysing company earnings. The agent builds its own profit forecast (top-down from GDP and industry growth, or bottom-up from revenue drivers), compares it with analyst consensus, and computes a standardised earnings surprise score (SUE). It also tracks how analysts are revising their estimates and frames the results as possible trading signals, using Chinese A-share reporting dates and conventions. The output follows a fixed report template. The skill is explicitly framed for research and backtesting, not investment advice.

Great for

  • Quantitative researchers testing post-earnings drift or estimate-revision strategies on Chinese A-shares
  • Analysts who want a consistent template for comparing their own EPS forecasts with consensus
  • Students learning how earnings surprise and analyst revision signals are constructed

Skip it if

  • Making real buy or sell decisions without independent verification: the thresholds are illustrative and the skill itself says it is not investment advice
  • Users without paid data terminals (Wind/Choice) who need timely consensus figures, since the file notes free sources may be too slow or incomplete
  • Non-A-share markets or small-cap stocks with few analysts, where the skill itself warns the consensus statistics are weak

Try asking

  • “Build a top-down EPS forecast for a Chinese consumer company and compare it with consensus”
  • “Calculate the SUE and analyst revision momentum for stocks in the CSI 300 index”
  • “Draft an earnings-surprise report with signal judgement and risk notes for a given A-share ticker”
  • “Set up a post-earnings-drift backtest with a holding period and SUE threshold”
Step-by-step guide: how to use Earnings Forecast & Consensus GapInstall, first run, examples, tips and FAQs

Install in 3 steps

  1. 1

    Download the skill

    The ZIP contains the 1 original files, the MIT licence and an attribution note.

    earnings-forecast.zip
  2. 2

    Add it to your agent

    Claude Code (all projects)

    mkdir -p ~/.claude/skills && unzip earnings-forecast.zip -d ~/.claude/skills/

    Claude Code / Agent SDK (this project only)

    mkdir -p .claude/skills && unzip earnings-forecast.zip -d .claude/skills/

    Claude apps (web/desktop): Settings → Capabilities → Skills → Upload skill, and choose the ZIP.

  3. 3

    Ask for the task

    No special command needed — the agent reads the skill's description and loads it when your request matches. Try one of the prompts above.

Get better results

  • Supply your own consensus and historical data; the agent cannot verify figures from the skill text alone, and the examples (e.g. Kweichow Moutai EPS) are illustrative.
  • Check the thresholds (SUE ±1.5/2.0, ERM ±0.3) against your own backtest before relying on them, since the file labels them as reference values.
  • Always review the risk section for one-off gains, accounting changes and goodwill impairment, and use the non-recurring-adjusted EPS the skill recommends.

What's inside

  • SKILL.md

Redistributed unmodified from HKUDS/Vibe-Trading under the MIT licence. The assessment was drafted with AI from the skill's files on 2026-10-29. Skills can instruct your agent to run code — read SKILL.md and any scripts before installing.