What Legitimate AI Trading Actually Looks Like

Before diving into how AI trading fraud works, Felix Bick’s How Not to Get Scammed by AI Trading Apps does something many similar books skip: it establishes what legitimate AI-assisted trading genuinely looks like, giving readers an essential baseline for comparison.

Chapter 9 breaks legitimate AI trading into a few real categories: quantitative signal generation using statistical models to flag potential trade setups, execution optimization to minimize slippage on large orders, risk management flagging portfolio concentration or unusual volatility, and sentiment analysis scanning news or social media for market-moving signals. Bick notes these systems are built by teams with quantitative finance backgrounds, tested extensively against historical data, and — critically — still lose money in a meaningful share of trades, because markets are only partially predictable.

This last point is essential to the book’s entire argument. As Bick writes, real quantitative funds rarely market directly to retail consumers with promises of guaranteed daily returns. Their edge, if genuine, is often modest — a few percentage points of outperformance annually — and closely guarded, since publicizing a working strategy invites competitors to erode its effectiveness.

Bick draws the natural conclusion: anything claiming to dramatically exceed what the most sophisticated, well-funded quantitative funds in the world achieve should be treated as an extraordinary claim requiring extraordinary evidence.

This grounding chapter is genuinely valuable precisely because it doesn’t dismiss AI trading wholesale — it establishes a realistic baseline that makes fraudulent claims easier to spot by contrast. Readers walk away understanding not just what to distrust, but what genuine, credible AI trading actually resembles in practice.

This foundational honesty is part of what distinguishes How Not to Get Scammed by AI Trading Apps from more sensationalized treatments of the topic — Felix Bick clearly wants readers equipped with real understanding, not just fear.