Below you will find pages that utilize the taxonomy term “Trading”
Bear Market Warning: Why This Choppy Action Feels Like the Early Stages of a Prolonged Downturn (March 2026 Update)
The last few weeks have been brutal for anyone trying to trade directionally. The market’s been extremely choppy—spiky up days followed by sharp reversals, massive short squeezes, and volatility that’s starting to feel less like a healthy correction and more like the drawn-out grind we see in the early phases of bear markets.
I don’t usually jump into frequent market commentary—I’m more focused on building tools and community at retailtrader.ai—but the recent price action has me paying close attention. Here’s a breakdown of what I’m observing right now.
The Ugly Truth: The $730 Billion Elephant in the Room: Why SoftBank Could Be the Pin That Pricks the AI Bubble
As a retail trader, my bread and butter is the short-term: momentum, technical breakouts, and rapid execution. But surviving in the markets requires periodically stepping out of the trenches. It requires adopting a contrarian, long-term philosophy—akin to the legendary Ken Fisher—that forces you to question the prevailing noise, look at market history, and spot the macro risks that everyone else is too euphoric to see.
Right now, the market is blindingly euphoric about Artificial Intelligence. But if you zoom out and look closely at the financial engineering funding this boom, you’ll spot a massive elephant stomping around the room: SoftBank Group (SFTBY).
The Ugly Truth: The End of the $1M Seed Round: Bootstrapping with AI & Zero CAC
I was at an investor meeting the other day. It wasn’t for my own company, but I got to watch a lot of founders proudly talking about their businesses. It reminded me of all the posts you see on LinkedIn where people brag about raising $10 million from a venture capitalist like it’s the ultimate achievement.
The Ugly Truth: Results Over Mission: How AI and Multidisciplinary Thinking Elevated My Trading Portfolio
A few days ago, I hosted a webinar where I spoke about the highly public collapse of my former company.
I learned the hard way that tangible results often matter more than blind commitment to a company mission—because let’s face the ugly unspoken truth: your mission statement goes out the window when your results don’t speak for themselves.
Below are screenshots from my E*TRADE account showing my performance and value views across the 6-month and 2-year tabs, alongside a snapshot of my verified Kinfo stats showing my win rate and profit across 131 trades.
Introducing the retailtrader.ai Model Account
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. 🎳
Curated Trades Update: 50% Returns in a Volatile Market
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
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.
A Tale of Two Cities: Market Divergence & The 'Founder Incentive'
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
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:
