At retailtrader.ai, we are always looking at ways to stand out from the crowd—especially given the number of “fake gurus” in this space. Thinking from first principles and being different is an integrated part of our DNA. 🧬

That is why we are introducing the “retailtrader.ai Model Account,” which showcases our third-party independently verified trading performance. ✅

The “Aha!” Moment 💡

As I was driving back after taking my son out bowling this afternoon, I had an interesting thought. I’ve mentioned in previous videos that I’m not a big fan of posting screenshots of my personal account. 🎳

Happy Super Bowl Sunday, everyone.

While you’re waiting for kickoff, I wanted to share a quick update on our flagship feature: Curated Trades.

The market has been extremely volatile over the last couple of weeks. Tech stocks have been decimated, and many portfolios are seeing red. We launched our Curated Trades engine right in the midst of this chaos, so I was curious myself to see how the model would handle the stress test.

The most dangerous thing in trading isn’t volatility. It’s isolation.

Most retail traders fail because they are trying to beat institutional algorithms while sitting alone in a room. They have the charts, but they don’t have the conviction.

At retailtrader.ai, we solved the data problem first. Our neural networks scan the market 24/7 to find high-probability setups (like the $AAPL and $NVDA signals we caught last week).

But data is only half the equation. Execution is the other half.

It’s been like a “Tale of Two Cities” in the markets recently.

On one hand, you have second-tier tech stocks getting decimated. If you are holding these, you see no hope, and you might be waiting years for them to bounce back—if they ever do.

On the other hand, you have stocks like Alcoa, Restoration Hardware, Occidental Petroleum, and Kratos Defense that have been absolutely flying nonstop. Just look at the Alcoa chart and you’ll see exactly what I mean.

Selectivity vs Volume: Why Selection is the Ultimate Force Multiplier

In quantitative trading, the validity of a strategy is only as good as its constraints. At retailtrader.ai, we utilize an Exact Parity Simulator that treats our strategy with the same rigor as a professionally managed fund. Our latest results reveal a compelling narrative: algorithmic selection transforms raw market signals into institutional-grade alpha.

Context of Performance

• Out-of-Sample Data: These results represent live data tracked since our launch in Nov 2025, representing ~50 days. While the metrics are subject to short-term compounding due to the short time window, it demonstrates the general efficacy and the positive alpha of the methodology used.
• Normalization: We fully expect these extraordinary figures to normalize as market conditions shift.
• Live Signals: This simulation shows how the system would have performed if you followed the actual live signals delivered to our users since our launch in the real-world environment.

1. Experimental Design: The “Physics” of the Forward-Simulation Test

Most retail systems generate massive mental stress by forcing users to chase nanosecond ticks. We reject that model in favor of First Principles. Our architecture is specifically tailored for a “Fire and Forget” approach: