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agent-trading-predictor

Predicts and executes trades using temporal advantage calculations and sublinear algorithms.

70.1k|8.4k|Updated Jun 2, 2025
Search Tags:#risk management#portfolio optimization#trading#prediction#sublinear algorithms#high-frequency#latency arbitrage
One-click install
npx skills add https://github.com/ruvnet/claude-flow --skill agent-trading-predictor
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: agent-trading-predictor
Source: https://github.com/ruvnet/claude-flow/tree/main/.agents/skills/agent-trading-predictor
Command: npx skills add https://github.com/ruvnet/claude-flow --skill agent-trading-predictor

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

It addresses the challenge of reacting to market data faster than traditional trading systems by computing predictions before data physically arrives, enabling latency arbitrage and real-time risk assessment.

Core Features & Use Cases

  • Temporal Advantage Trading: Calculate computational lead times over light-speed data transmission between markets (e.g., Tokyo to NYC) and execute predictive trades.
  • Portfolio Optimization: Solve large covariance matrices with sublinear algorithms for real-time portfolio construction and Value at Risk calculations.
  • Multi-Agent Coordination: Coordinate trading signals, risk consensus, and execution across distributed agent swarms via Claude Flow and Flow Nexus sandboxes.
  • Use Case: A quantitative trader computes the temporal advantage for a Tokyo-NYC route, validates the lead exceeds the arbitrage threshold, and executes a cross-market trade before the market data arrives.

Quick Start

Ask the agent to calculate the temporal advantage for a Tokyo to NYC trading route and execute a predictive trade if the lead exceeds 50 milliseconds.

Frequently Asked Questions about agent-trading-predictor

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

FAQPage Schema
How do I calculate temporal advantage for high-frequency trading?▼

Use the calculateLightTravel tool with the distance in kilometers between markets and your matrix size representing portfolio complexity. It returns light travel time, computation time, and the resulting advantage in milliseconds.

How to execute a predictive trade before market data arrives?▼

Call predictWithTemporalAdvantage with your portfolio risk matrix, market signal vector, and the distance to the market. The sublinear solver computes the prediction faster than the data can physically transmit.

What is latency arbitrage between geographic markets?▼

Latency arbitrage exploits the delay in data transmission between distant markets, such as Tokyo and NYC or satellite links. When computational lead exceeds transmission time, trades can execute on information before it arrives.

Can this trading agent integrate with Claude Flow swarms?▼

Yes, it supports multi-agent trading swarms for distributed market data processing, signal aggregation, and consensus-based risk decisions. It also integrates with Flow Nexus for sandboxed execution and LSTM neural network training.

What are the limitations of temporal advantage trading?▼

The approach depends on the computational lead exceeding transmission latency, which requires sufficiently large matrix problems and long distances. It also assumes access to the sublinear-time-solver MCP server and does not guarantee profitable trades.

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