Skip to content

Latest commit

 

History

History
50 lines (34 loc) · 2.6 KB

File metadata and controls

50 lines (34 loc) · 2.6 KB

Lambda Investing Framework Documentation

This index provides a guide to the comprehensive documentation of the Lambda Investing trading framework. The following documents provide deep insights into the system architecture and implementation details that are particularly valuable for LLMs performing in-depth reasoning and analysis.

Core Documentation

The foundational architecture document explaining the Algorithm abstract class that powers all trading strategies. This documentation covers the event-driven architecture, lifecycle management, market data processing, order handling, position tracking, and P&L calculation. Understanding this core class is essential for any reasoning about how algorithms interact with the market and manage state in the framework.

Detailed explanation of the four market making algorithm implementations: AvellanedaStoikov, AlphaAvellanedaStoikov, AlphaConstantSpread, and ConstantSpreadAlgorithm. This document covers theoretical foundations, mathematical models, parameter impacts, and implementation details. Critical for understanding the nuances of market making logic, inventory management, and alpha signal integration.

Comprehensive guide to the backtest system that enables simulation and evaluation of trading algorithms. This document explains configuration formats, execution flow, data management, reinforcement learning integration, and performance analysis. Essential for understanding how algorithms are tested, how market conditions are simulated, and how performance metrics are calculated.

Grafana dashboards for real-time observability: application logs, JVM performance, end-to-end latency statistics, algorithm trades & execution, portfolio PnL, and throughput statistics. Includes setup notes for Loki, Prometheus, and dashboard import.

How to Use This Documentation

These documents provide multi-layered insights that support:

  • Understanding the system architecture and design patterns
  • Analyzing algorithm implementations and mathematical models
  • Tracing data and control flow through the system
  • Reasoning about parameter impacts and optimization
  • Diagnosing potential issues and edge cases
  • Extending the framework with new algorithms or features

Each document contains implementation details, theoretical foundations, and practical examples that can inform deep reasoning about the system's behavior under different market conditions.