How accurate is ZARQ at predicting token collapses?

ZARQ demonstrates high accuracy, achieving 100% death recall (every token collapse detected out-of-sample) and 98% precision, with only one genuine false positive in its extensive validation.

What core risk analysis features does ZARQ provide?

ZARQ offers full Trust Score ratings (A+ to F) with a 5-pillar breakdown, Distance-to-Default analysis with 7 distress signals, and active structural collapse and stress warnings/alerts to identify risks proactively.

Can ZARQ be used for real-time pre-trade safety checks?

Yes, ZARQ is designed for rapid pre-trade safety validation. Its 'crypto_safety_check' tool provides responses in under 100ms, enabling quick, informed decisions before executing trades.

ZARQ

Name: ZARQ
Author: zarq-ai

byzarq-ai

0•

开发者工具

分析与监控

安全与测试

Delivers independent crypto risk intelligence through Trust Score ratings, Distance-to-Default analysis, structural collapse warnings, and pre-trade safety checks for numerous tokens.

ZARQ provides comprehensive crypto risk intelligence, leveraging the Model Context Protocol (MCP) to offer crucial insights into the stability and safety of digital assets. It delivers detailed Trust Score ratings, performs sophisticated Distance-to-Default analysis to predict potential collapses, issues proactive structural collapse warnings, and conducts rapid pre-trade safety checks for 198 tokens. With a proven track record of 100% death recall and 98% precision in detecting token collapses, ZARQ empowers users with timely, actionable data to navigate the volatile crypto market securely.

主要功能

010 GitHub stars

02Quick pre-trade safety validation (<100ms response time)

03Distance-to-Default analysis with 7 distress signals

04Active structural collapse and stress warnings/alerts

05Full Trust Score ratings (A+ to F) with a 5-pillar breakdown

06High accuracy in predicting token collapses (100% recall, 98% precision)

使用案例

01Performing rapid pre-trade safety validation for cryptocurrency tokens.

02Monitoring for early structural collapse or stress signals in the crypto market to prevent losses.

03Assessing the overall risk and trust level of various digital assets through detailed ratings.