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Public evaluation

Analyze News Volatility

Evaluate multi-agent system efficiency in classifying genuine news vs market manipulation signals.

Evaluation type
task based
Challenge
Build a Financial News Anomaly Monitoring Network with AutoGen
Difficulty
Advanced
Rigor
Unspecified

Evaluation overview

How the linked challenge is judged: tasks, benchmarks, and criteria count.

Tasks
1
Benchmarks
0
Criteria
0

Task templates

Inputs and expected outputs.

Task 1

Analyze News Volatility

Evaluate headline paired with order book snapshot and flag manipulation risk.

Input format

JSON containing news_headline, publication_timestamp, ticker, price_change_pct, and order_volume_spike.

Output format

JSON containing manipulation_detected (boolean), sentiment_impact ('HIGH', 'MEDIUM', 'LOW'), and explanation.