"It’s not just about being fast." When we talk about "Low Latency" in software engineering, we usually mean raw speed—how fast can I get a packet from A to B? But in algorithmic trading, there is a second, equally critical metric: Temporal Precision. If a signal says "Execute CALL at 18:40:00," executing at 18:40:01 is a failure. Executing at 18:39:59 is a disaster.
I recently started building a "headless" trading bot—one that ignores charts and indicators entirely in favor of strict, text-based signals from Telegram. Here is how I approached the tech stack selection for a system where timing is everything, and why I eventually landed on Go
Before picking a language, I broke down exactly what the bot needed to do. It wasn’t just "buying stocks." The requirements were…
"It’s not just about being fast." When we talk about "Low Latency" in software engineering, we usually mean raw speed—how fast can I get a packet from A to B? But in algorithmic trading, there is a second, equally critical metric: Temporal Precision. If a signal says "Execute CALL at 18:40:00," executing at 18:40:01 is a failure. Executing at 18:39:59 is a disaster.
I recently started building a "headless" trading bot—one that ignores charts and indicators entirely in favor of strict, text-based signals from Telegram. Here is how I approached the tech stack selection for a system where timing is everything, and why I eventually landed on Go
Before picking a language, I broke down exactly what the bot needed to do. It wasn’t just "buying stocks." The requirements were:
- Signal Parsing
- The "Wait"
- Concurrency
- State Recovery (The Martingale Logic)
The Contenders: Python vs. Node.js vs. Go
- Python Pros: The king of finance. Great libraries (Pandas, TA-Lib) and easy syntax.
The Dealbreaker: The Global Interpreter Lock (GIL) and Threading. While Python can do concurrency, managing precise microsecond-level timers while processing heavy logic in other threads can get messy. time.sleep() is blocking, and asyncio adds complexity when you need absolute precision rather than just "non-blocking" I/O
- Node.js Pros: Amazing I/O handling. Perfect for listening to Webhooks.
The Dealbreaker: It’s single-threaded by default. If the CPU gets busy calculating a Martingale recovery for one trade, it might block the event loop just long enough to delay the execution of another trade by a few milliseconds. In this game, those milliseconds cost money.
- Go (The Winner) Why it won: Go combines the compilation speed of C with the ease of Python, but its superpower is Goroutines
In the end, Go won this round because it treated "Time" as a first-class citizen. It allowed me to build a bot that sleeps efficiently and wakes up aggressively.
But software engineering is about trade-offs. I’m writing this to document my thought process, but I’m eager to learn from yours.
So, a question for the comments: If you were building a system that had to execute a task at an exact millisecond, what stack would you pick today, and why?