Jedi AutoTrader

I. High-Level Software Architecture Outline

Building a Robust Auto Trading Agent requires a Meticulous Multi Layered Approach

Module 1 Data Ingestion & Pre-Market Scanning Engine

Purpose

Gathers & pre-processes all Necessary Data before the market opens

Components

• Data Connectors APIs to market data providers & news sources
• Data Types Real-time & historical spot prices, macro-economic indicators, market sentiment indicators, technical indicators
• Pre-Scan Routine Scheduled job that runs market analysis & generates Morning Report

Module 2 Strategy & Decision Engine (The Brain)

Purpose

Analyzes data & makes all Trading Decisions

Components

• Algorithm Library Collection of strategy logic
• Test Trade Logic Isolates small capital to gauge Market Volatility
• Adaptive Logic Adjusts parameters based on test trade outcomes
• Signal Generator Generates Buy Sell Signals for main sessions

Module 3 Execution & Order Management System (OMS)

Purpose

Safely executes trades & manages Open Positions

Components

• Broker API Connector Direct link to brokerage account
• Order Router Formats signals into specific orders
• Verification Layer (Critical) Double-checks all orders before execution

Module 4 Risk & Compliance Manager

Purpose

The ultimate Safety Net that enforces rules to protect capital

Components

• Pre-Trade Checks Hard limits on position size & exposure
• Real-Time Monitoring Continuous monitoring of drawdown & margin usage
• Circuit Breaker Automatic pause shutdown triggers
• Logging Comprehensive audit trails

Module 5 Reporting & Dashboard Interface

Purpose

Human oversight & system analysis

Components

• CLI for Development Text-based output for debugging
• Web Dashboard (Future State) Visual display of P&L & system health
• Alert System Email SMS alerts for trades & errors

II. Critical Questions for Development (Phase 1)

To build this correctly, we need to answer these Critical Questions first

1. Brokerage & Data Infrastructure

• Which brokerage firm with reliable API for Automated Trading
• Primary market data provider & Backup Options
• What are the Latency Requirements

2. Core Strategy Definition (“Best Practices”)

• What specific, proven strategy will we implement first
• Exact logic for test trade & Adaptive Rules

3. Risk Management Parameters

• Total account Capital Allocation
• Maximum capital per trade & Daily Loss Limits
• Stop-loss logic & parameters

4. Verification & Due Diligence

• Specific steps for the Auto Verify Function
• Pre-trade simulation & Validation Processes

5. Deployment & Environment

• Where will the agent run (Cloud Server vs Local Machine)
• Handling of daylight saving & Market Holidays
• Version control & Deployment Pipeline

III. Proposed Development Plan (Step-by-Step)

Phase 0 Setup & Discovery

Answer critical questions, select broker, define Initial Strategy, set up development environment

Phase 1 Build Core Modules (Paper Trading Only)

Develop Data Ingestion Engine, Broker Connector in simulated mode, basic Strategy Logic, & Risk Manager

Phase 2 Implement Verification & Safety Layers

Code Verification Layer, build Circuit Breaker Logic, enhance logging for audit trails

Phase 3 Develop the Adaptive Logic

Code test trade execution & algorithms for Parameter Adjustment based on results

Phase 4 Backtesting & Simulation

Run agent against 1-2 Years of Historical Data, analyze performance metrics, refine parameters

Phase 5 Live Deployment (With Extreme Caution)

Switch to live account with Minimal Capital, enable features gradually, constant monitoring

Phase 6 Scaling & Expansion

Add sophisticated strategies, expand to other metals, build Web Dashboard for monitoring

System Component Breakdown

Implementation Plan

Phase 1 Build the Foundational Dashboard

Start by creating the Multi-Timeframe Monitoring Dashboard for your watchlist

Phase 2 Develop the Pre-Market AI Analyst

Focus on the system that runs before the market opens

Phase 3 Create the Intraday Guidance Engine

Add Real-Time Analysis Capabilities

Phase 4 Introduce Controlled Automation

Connect analysis engines to brokerage account via API for Automated Execution