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consolidated-tape-nbbo

Consolidates real-time trading data from multiple venues for NBBO reconstruction and trade-through surveillance.

Updated Feb 10, 2026
Search Tags:#latency#market data#surveillance#nbbo#consolidated tape#trade-through
One-click install
npx skills add https://github.com/GhostOf0days/codex-quant-skills --skill consolidated-tape-nbbo
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: consolidated-tape-nbbo
Source: https://github.com/GhostOf0days/codex-quant-skills/tree/main/consolidated-tape-nbbo
Command: npx skills add https://github.com/GhostOf0days/codex-quant-skills --skill consolidated-tape-nbbo

SYSTEM DOCUMENTATION & REQUIREMENTS

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

What problem does it solve?

This Skill addresses the complexity of consolidating real-time trading data from multiple venues to accurately reconstruct the National Best Bid and Offer (NBBO) and detect trade-through violations.

Core Features & Use Cases

  • NBBO Reconstruction: Accurately rebuilds the NBBO by consolidating quotes from various trading venues.
  • Trade-Through Surveillance: Identifies and flags trades that execute outside the protected NBBO.
  • Latency Analysis: Analyzes latency differences between SIP and direct feeds to ensure data integrity.
  • Use Case: Monitor the integrity of the consolidated tape by ensuring NBBO is correctly calculated and that no trades violate protected quote rules, flagging any discrepancies for review.

Quick Start

Run the consolidated tape NBBO diagnostics script on the input CSV file.

Frequently Asked Questions about consolidated-tape-nbbo

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

FAQPage Schema
How do I reconstruct NBBO from multiple trading venues?▼

NBBO reconstruction consolidates real-time cross-venue trading data to calculate the National Best Bid and Offer. This Skill manages quote consolidation and applies protected quote logic to ensure accurate price discovery across fragmented markets.

How does trade-through surveillance detect violations on the consolidated tape?▼

Trade-through surveillance identifies and flags trades that execute outside the protected NBBO. By monitoring the consolidated tape, the system detects discrepancies where transaction prices bypass the best available quotes, flagging them for compliance review.

Can I analyze SIP and direct feed latency differences using Python and pandas?▼

Yes, latency analysis compares SIP and direct feed timing to ensure data integrity. Using Python scripts with pandas, you can run deterministic diagnostics on input CSV files to measure latency gaps and validate consolidated tape quality.

What is the best way to monitor consolidated tape integrity and NBBO quality controls?▼

Monitoring consolidated tape integrity requires continuous NBBO quality controls and cross-venue quote validation. This Skill provides production diagnostics and Markdown reference checklists to track data accuracy and flag violations for review.

Do I need a specific data format to run NBBO diagnostics?▼

You need to provide real-time trading data structured as an input CSV file. The Skill uses Python scripts with pandas and argparse to execute deterministic diagnostics on this data to evaluate NBBO reconstruction and detect trade-throughs.

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