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_old-earnings-orchestrator

Query Neo4j for 8-K filings and process earnings predictions chronologically.

3|1|Updated Dec 2, 2024
Search Tags:#orchestration#stock market#attribution#filings#prediction#neo4j#earnings
One-click install
npx skills add https://github.com/faisalanjum/EventTrader --skill old-earnings-orchestrator
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: _old-earnings-orchestrator
Source: https://github.com/faisalanjum/EventTrader/tree/main/.claude/archive/skills/_old-earnings-orchestrator
Command: npx skills add https://github.com/faisalanjum/EventTrader --skill old-earnings-orchestrator

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes scripts (resource) and references (resource) components.

What problem does it solve?

This Skill automates the complex process of analyzing a company's earnings filings, building a closed-loop system for prediction, attribution, and accuracy tracking.

Core Features & Use Cases

  • Chronological Filing Processing: Analyzes all 8-K earnings reports for a given company in the order they were filed.
  • Prediction & Attribution Loop: Predicts market reaction before filings and verifies against actual outcomes, learning from discrepancies.
  • Accuracy Tracking: Maintains running metrics on prediction accuracy (direction and magnitude).
  • Resume Capability: Can pick up from where a previous run was interrupted.
  • Use Case: A financial analyst can use this Skill to process all historical earnings reports for a specific stock ticker, gaining insights into the accuracy of past predictions and identifying patterns in market reactions.

Quick Start

Use the _old-earnings-orchestrator skill to process all earnings filings for the ticker 'AAPL'.

Frequently Asked Questions about _old-earnings-orchestrator

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

FAQPage Schema
How do I automate earnings analysis and prediction for 8-K filings?▼

You can automate earnings analysis by orchestrating a batch workflow that queries Neo4j for 8-K filings, processing each chronologically through prediction and attribution steps while tracking accuracy metrics.

How does prediction attribution work for stock market earnings reports?▼

Prediction attribution works by predicting market reaction before a filing is processed, then verifying the prediction against actual outcomes to learn from discrepancies and maintain running accuracy metrics.

Can I resume an interrupted batch earnings analysis run?▼

Yes, you can resume an interrupted earnings analysis run. The orchestration workflow includes resume logic that picks up from where a previous chronological filing processing job was stopped.

Do I need Neo4j to process historical earnings filings chronologically?▼

Yes, Neo4j is required. The batch earnings analysis workflow queries Neo4j to retrieve 8-K filings, which are then processed chronologically through prediction, attribution, and accuracy tracking steps.

What is the best way to track prediction accuracy for stock market filings?▼

The best way to track prediction accuracy is using a closed-loop orchestration workflow that processes 8-K filings chronologically, comparing predicted market reactions against actual outcomes to maintain running metrics.

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