How does it handle lookahead bias in financial data?

It uses strict data guardrails and filters that treat the 8-K filing timestamp as a hard cutoff, ensuring no future information (like subsequent stock price returns) influences the prediction.

Can I invoke this skill manually in Claude Code?

No, this skill is configured as non-user-invocable and is intended to be triggered by an orchestration agent within the EventTrader ecosystem.

Which model is required for this skill?

This skill is optimized for the claude-opus-4-5 model to ensure high-reasoning capabilities for complex financial analysis.

What is the primary purpose of the Earnings Prediction skill?

The skill is designed to predict the direction and magnitude of a stock's price movement immediately following an 8-K earnings release using only data available at that specific point in time.

What kind of output does the skill generate?

It produces a result.json file containing the predicted direction (up/down), magnitude (0-8%+), a confidence percentage, and a brief explanation of the reasoning.

Earnings Prediction & Stock Analysis

Name: Earnings Prediction & Stock Analysis
Author: faisalanjum

byfaisalanjum

•

데이터 과학 및 ML

Predicts stock price direction and magnitude following 8-K earnings releases using strictly point-in-time financial data.

The Earnings Prediction skill is a specialized AI capability designed for event-driven financial analysis. It automates the interpretation of 8-K earnings filings to forecast how a stock will react before the market fully incorporates the news. By strictly enforcing point-in-time (PIT) data guardrails, the skill eliminates lookahead bias, ensuring that all predictions are based solely on information available at the exact moment of the filing. It outputs structured data including movement direction, magnitude (from tiny to extreme), and a confidence score, making it an essential component for automated trading workflows and quantitative research.

주요 기능

012 GitHub stars

02Built-in data guardrails for financial compliance and accuracy

03Structured JSON output for seamless integration with trading systems

04Precise magnitude forecasting ranging from 0% to over 8% movement

05Strict point-in-time (PIT) data enforcement to prevent lookahead bias

06Automated analysis of 8-K filings and SEC accession numbers

사용 사례

01Automated event-driven trading strategy development

02Rapid sentiment analysis of SEC filings for institutional research

03Backtesting earnings reactions using historical PIT-safe datasets

What are Skills?·How to Install

Install with 🐟 Skill.Fish

npx skillfish add faisalanjum/eventtrader earnings-prediction

For use in Claude.ai and ChatGPT

Download Skill