Generate trading signals by forecasting EPS and computing SUE with PEAD logic.
npx skills add https://github.com/loanntc/Paave --skill earnings-forecast-loanntc
Please help me install this Agent Skill. Skill: earnings-forecast Source: https://github.com/loanntc/Paave/tree/main/skills/earnings-forecast Command: npx skills add https://github.com/loanntc/Paave --skill earnings-forecast-loanntc
This Skill helps you translate earnings forecasts and analyst-consensus expectations into a measurable “expectation gap” so you can identify potential post-earnings trading opportunities.
Use the earnings-forecast skill to generate an earnings expectation gap report for a target stock by applying Top-Down or Bottom-Up EPS forecasting, computing SUE and ERM, and outputting a signal assessment plus PEAD-style entry guidance.
High-intent search queries and answers about installing and using this skill.
To calculate SUE for PEAD trading signals, you normalize the forecast error by analyst consensus dispersion, then map the standardized unexpected earnings to post-announcement drift thresholds for entry guidance.
Generating equity trading signals involves modeling bottom-up or top-down EPS, computing SUE against consensus, and tracking analyst revision momentum (ERM) from upgrade and downgrade counts to quantify expectation gaps.
Analyst expectation revision momentum (ERM) is measured by quantifying the up and down analyst counts alongside the forecast-change magnitude, detecting whether consensus expectations are shifting favorably before earnings announcements.
Yes, top-down and bottom-up EPS forecasting outputs feed directly into an earnings-calendar-aware framework, providing structured entry and holding plans based on SUE thresholds and PEAD drift logic.
Standardized unexpected earnings requires normalized forecast-error dispersion to accurately scale the deviation between your EPS forecast and analyst consensus, ensuring cross-sectional comparability for post-earnings drift evaluation.
PEAD-style drift logic may not apply when analyst consensus data is sparse or forecast-error dispersion is abnormally high, as these conditions distort SUE thresholds and undermine the reliability of post-earnings drift signals.
ebrahim-saniCompare EPS forecasts with consensus to compute SUE and generate PEAD signals.
wudyeAnalyze earnings estimate revisions and guidance changes to forecast post-earnings price drift.
wudyeForecast EPS and compare against consensus to generate SUE/ERM trading signals.
charliedream1Track analyst estimate revisions and earnings surprises for US and Hong Kong equities.
