Building a Production-Ready Position Manager for Algorithmic Trading

Short summary

This article documents the architectural evolution of a Position Manager component for a Python algorithmic trading platform, part of an 18-part engineering series. The author explains how naive variable-based state tracking breaks down as features like partial take profit, break-even, trailing stops, and futures leverage are added. The core insight is that a position is a business object with history, not a loose collection of prices, and event-driven state management becomes essential for reliability.

• •Naive variable-based position tracking fails as trading features grow in complexity
• •A position should be modeled as a business object with history, not loose variables
• •Event-driven architecture is needed for reliable position lifecycle management

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