Findash Octopus Architecture Guide

Overview

This guide details the modular, 11-agent architecture of the Findash Octopus Trading Platform. It serves as a critical reference point for developers ensuring that changes made to any specific agent module or the central intelligence orchestrator maintain system consistency and pipeline safety.

Adherence to this map ensures that specialized functionalities—from data ingestion to risk management—are updated in isolation, preventing cascading failures across the complex trading ecosystem.

Capabilities

• M1 Data Collector: Handles all external data acquisition via web scraping and API fetching.
• M2 Data Warehouse: Manages structured storage, retrieval, and indexing of processed market data.
• M3 Real-time Processor: Processes incoming data streams for immediate analysis and alerting.
• M4 Strategy Agent: Responsible for generating actionable trading signals using defined strategies.
• M5 ML Models: Executes core machine learning tasks like classification and prediction.
• M6 Risk Manager: Assesses portfolio risk, ensuring compliance with predefined operational limits.
• M7 Price Predictor: Focuses on advanced time-series forecasting for future price movements.
• M8 Paper Trader: Simulates live trading execution without using real capital.
• Orchestrator: Coordinates the workflow between all 11 specialized agents.

Example Use Cases

When implementing a new feature, such as incorporating alternative data feeds, you must coordinate changes across multiple modules. For instance, updating the data ingestion process requires modifying M1 (Data Collector) and ensuring the schema updates are correctly indexed in M2 (Data Warehouse) before any downstream agent like M4 (Strategy Agent) can utilize the new data for signal generation.

Alternatively, if improving prediction accuracy, changes to M7 (Price Predictor) must be validated against historical backtesting runs managed by M4 and monitored for compliance adherence via M6 (Risk Manager).