Our users generated $68K in realized P&L through Atlas since May. Here is what we learned.
966 closed positions. 57.9% hit rate. $70 average gain per trade. We built Atlas to help retail investors follow their own strategies consistently. Turns out when you remove the human error from execution, the numbers get interesting fast.
The interesting part here is that the raw P&L numbers don't necessarily tell you what is actually driving the outcome. A 57.9% hit rate can look strong, but the real question is which part of the system is responsible for the improvement—and whether that holds across different user strategies.
Fair point. The hit rate is a byproduct of user strategies, not something Atlas directly optimizes for. What we do control is removing the execution gap between what someone planned to do and what they actually did. That's where we see the clearest delta. Breaking it down by strategy type is next on our roadmap.
That’s an interesting distinction — separating what users bring from what Atlas actually changes. I’d be curious to see what the strategy-level breakdown reveals once you have it.