At 08:15 this morning, I pulled the logs from four autonomous trading bots that had run overnight. The total P&L: -$19,220 simulated across 71 trades. But not all losses are equal. Inside those logs were the fingerprints of exact mechanical bugs, verified fixes, and more importantly, several potentially lucrative edges that the bots were not designed to exploit.
This article is a deep-dive into that session. We’ll cover:
What exactly happened, bot by bot
Which fixes worked and which failures remained
The market’s overnight tape regime
Eight quantitative research formulas/algorithms extracted directly from the failure
Python code for each algorithm so you can test them yourself
Before we go on: this was a simulated account, not real money. But the patterns are real. Losses are tuition, and this session was a full-blown masterclass.
