Taming the Trading Beast: Overcoming KIS API Rate Limits in My Auto-Trading Engine

Context: Building a Robust Auto-Trading System

In my ongoing project to develop a reliable auto-trading bot for U.S. stock trading, system stability has been a crucial objective. The trading engine’s capacity to accurately and swiftly manage operations like balance checks, order execution, and portfolio synchronization can mean the difference between a successful trading day and significant setbacks.

The Problem: Battling the EGW00201 Error

During recent trading operations, the system was plagued by frequent encounters with the dreaded EGW00201 error. This error, triggered by the overzealous rate limiter of our brokerage’s API, was particularly problematic during intensive data retrieval and balance check procedures. The relentless assault of rate limit hits was a significant barrier, disrupting not only balance checks but also data fetching operations critical to the system’s trading logic.

The Solution: Exponential Backoff and Enhanced Retry Logic

The primary solution hinged on optimizing API request strategies and strengthening error handling mechanisms.

• API Rate Limit Resolution: We implemented a global exponential backoff retry mechanism for handling 500-level errors and rate limits effectively. By meticulously recalibrating the delay intervals between API calls, the system now aligns strictly with the KIS API constraints.
• Enhanced Error Handling: I refactored the executeWithRetry logic to manage transient network failures such as ECONNRESET and timeouts gracefully. Enhanced error logging now helps in discerning between critical system halts and transient errors that allow for retry attempts.

Key Learnings

The journey of tackling these technical challenges was enlightening. I learned the necessity of balancing aggression with prudence when interacting with external APIs, especially in high-frequency environments. Effective error handling not only prevents system crashes but also improves resilience against unpredictable disruptions.

Next Steps

With a stable infrastructure now in place, the focus shifts to refining the core trading strategies. Specifically, I’ll be working on enhancing the ‘Momentum/Vol’ trading logic and implementing a ‘Daily Profit Goal’ feature. The aim is to dynamically manage risk and reward limits, ensuring that the trading bot not only executes efficiently but also adheres to set financial objectives.