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Trading Engine Architecture

Overview

The trading engine is designed with a modular architecture focusing on:

Separation of concerns
Thread safety
Error handling
Performance optimization

Core Components

1. Data Layer

Fetches data from multiple sources
Processes real-time market data
Manages historical data

2. Strategy Layer

Generates trading signals
Performs technical and market analysis

3. Risk Management

Handles position sizing
Enforces risk limits
Manages portfolio-level risk

4. Order Execution

Routes orders
Manages execution
Tracks order status

Data Flow

Market data ingestion
Strategy processing
Risk assessment
Order execution
Position/Portfolio update

Threading Model

Main thread: Coordinates the event loop
Data thread: Processes market data
Execution thread: Manages orders
Risk thread: Calculates risk metrics

Error Handling

Defined exception hierarchy
Comprehensive logging system
Built-in recovery mechanisms

Performance Considerations

Lock-free queues for inter-thread communication
Memory pooling for efficient resource usage
Cache optimization for faster data access

Deployment Guide

Prerequisites

C++17 compatible compiler
Python 3.8+
CMake 3.12+

Dependencies

spdlog
pybind11
Boost
nlohmann_json

Build Instructions

Linux/macOS
Windows

Configuration

Copy config.example.json to config.json
Update API keys and trading parameters
Set risk limits

Running

Monitor logs: logs/trading_engine.log
Watch system metrics
Review error reports

Troubleshooting

Data connection issues
Order execution errors
Risk limit violations