Recently, I’ve noticed more and more people discussing quantitative trading. I have to say, this topic is indeed easy to misunderstand. Many retail investors encounter so-called quantitative trading systems that are actually just buying other people’s apps or code scripts. The problem here is obvious—if this stuff really could make people consistently profit or even make money forever, why would the creators still need to sell it? The logic is simple, but many people just can’t see it.

Let’s first talk about what true quantitative trading really is. Simply put, it’s using mathematical models and computer programs to make trading decisions, analyzing vast amounts of historical and real-time data to automatically identify opportunities, generate signals, and execute buy and sell orders. It sounds impressive, but at its core, it’s just one sentence: using data-driven strategies to perform automated trading.

Real knowledgeable quantitative firms, like Fantom Quant, have you seen them come out and sell apps or trading systems? No, right? They mainly provide asset management services through Liang Wenfeng and his team, and don’t need to sell systems to make money. That’s the difference.

Most of the so-called quantitative trading tools on the market today, honestly, are not as good as studying the built-in trading bots and strategy functions of some mainstream exchanges. Those are developed by professional teams, tested in real markets, and have higher transparency.

Let’s also look at what retail investors can access in terms of quantitative trading. Honestly, most of the time, it’s simplified automated trading tools—based on basic indicators like moving average crossovers, price grids, and similar. They set some simple rules, and then the robot automatically executes trades. Some more advanced ones allow adjusting strategy parameters, but they are still far less complex than institutional-grade mathematical models. The entry barrier is indeed low, but don’t expect to get rich overnight.

What are the real advantages of quantitative trading? Strong objectivity, consistent execution, and the ability to handle massive data without being affected by emotions. But the limitations are also clear: models are based on historical data, and they tend to fail during black swan events; over-optimization can lead to overfitting traps.

What I want to say is that many people now promote quantitative trading just like they promote quick wealth—both are traps. Truly successful quantitative trading requires three conditions: high-quality strategies, strict risk control, and disciplined execution. None of these are easy.

Final advice: don’t always think about taking shortcuts. If there really were such simple ways to get rich, the creators would have used them long ago, and it wouldn’t be available to you. Blockchain opportunities are indeed plentiful, but the key is patience and steady effort. True wealth comes from persistent accumulation, not from fantasies of overnight riches. Calm down, take it step by step, and you’ll find that the distance to success isn’t that far.