event-driven

Analyze CSV event data with sentiment scoring to generate trading signals.

Updated May 25, 2026

Search Tags:#sentiment analysis #technical analysis #trading signals #event-driven trading #CSV data processing

Ready to run

npx skills add https://github.com/NigarumOvum/AutoTrading --skill event-driven-nigarumovum

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: event-driven
Source: https://github.com/NigarumOvum/AutoTrading/tree/main/Vibe-Trading/agent/src/skills/event-driven
Command: npx skills add https://github.com/NigarumOvum/AutoTrading --skill event-driven-nigarumovum

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires pandas, numpy, and includes scripts (resource) and references (resource) components.

What problem does it solve?

This Skill automates event-driven trading by analyzing sentiment and impact magnitude from news, announcements, and macro events, streamlining the process of generating trading signals.

Core Features & Use Cases

Event Analysis: Processes news, announcements, and macro events to score sentiment.
CSV Data Management: Manages event data in CSV format, providing a structured data layer.
Signal Aggregation: Combines event and technical signals through weighted aggregation for trading decisions.
Use Case: For a trader looking to integrate event-driven signals into their trading strategy, this Skill can be used to automate the analysis of market events and generate timely trading signals.

Quick Start

Activate the event-driven skill and provide the event CSV file to process and generate trading signals.

Frequently Asked Questions about event-driven

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

FAQPage Schema

How do I generate trading signals from news sentiment and CSV event data?▼

Yes, you can automate event-driven trading by feeding CSV-formatted market news and announcements into this Skill. It processes the CSV data, applies sentiment and impact magnitude scoring, and outputs aggregated trading signals without requiring manual analysis of each event.

Does this event-driven trading strategy combine sentiment analysis with technical signals?▼

Yes, event-driven trading strategies can combine sentiment analysis with technical signals through weighted signal aggregation. This Skill specifically combines event sentiment scores with technical indicators to produce a unified trading decision, ensuring market events are contextualized alongside price action.

Do I need pandas and numpy to process CSV data for event-driven trading?▼

No, this Skill does not require live API market feeds; it is designed to process CSV event data directly. You simply provide a structured CSV file containing news, announcements, and macro events, and it applies sentiment scoring to generate actionable trading signals.

What is the best way to score market event impact for an event-driven trading strategy?▼

The best way to score market event impact for an event-driven trading strategy is to use automated sentiment analysis on news and announcements. This Skill evaluates the impact magnitude of macro events and converts qualitative data into quantitative, sentiment-scored signals for trading decisions.

What are the limitations of using CSV data for event-driven trading signals?▼

A limitation of using CSV data for event-driven trading signals is the reliance on static, pre-formatted files rather than real-time market feeds. This approach requires you to manually source and structure news, announcements, and macro events into CSV format before analysis can occur.