Recently, I've seen quite a few discussions about quantitative trading, and honestly, I'm a bit surprised. This stuff is actually quite high barrier for retail investors; most people only come into contact with apps or script codes created by others. But there's a very simple logic behind it—if someone really makes money through quantitative trading, even consistently profits, why would they sell software? This question is worth pondering.

What exactly is true quantitative trading? Simply put, it’s using mathematical models and computer programs to drive trading decisions, relying entirely on data and algorithms rather than human intuition. It depends on a large amount of historical and real-time data, identifying opportunities, generating signals, and executing trades through automated systems. It sounds sophisticated, but the core logic is just replacing emotion with data.

Look at leading institutions like Fantom Quant, founded by Liang Wenfeng—do they sell quantitative trading software? No. Their real quantitative trading involves providing asset management services to internal or institutional clients, not retail sales. What does this indicate? Truly profitable quantitative trading doesn’t rely on selling software to survive.

Currently, what everyone calls “quantitative trading” on the market is actually far from institutional-level stuff. In simple terms, it’s some automated trading tools—based on basic rules (like moving average crossovers, grid trading, etc.)—that automatically generate signals or execute trades. The barrier has indeed lowered, and ordinary people can use it, but fundamentally, it’s still just programmatic trading tools, not real quantitative trading.

Most retail-accessible quantitative trading systems are just using existing platforms or bots, setting up some basic indicators for automatic operation. Honestly, many so-called “quantitative trading systems” are not even better than using Binance’s built-in trading bots and strategy tools. At least the exchange’s tools are stable, while most of those sold outside are full of pitfalls.

I don’t deny the advantages of quantitative trading—objective, consistent, efficient processing of big data. But the limitations are obvious: models are based on historical data, and during black swan events, they can fail outright; over-optimization can lead to “overfitting,” looking good in backtests but losing money in live trading. That’s why successful quantitative trading requires continuous optimization and risk management, not a static setup.

What I want to say is, don’t always think about taking shortcuts. If there really was an easy method to get rich quickly, the creators wouldn’t share it so easily. Blockchain opportunities are indeed plentiful, but the key lies in patience and discipline. Choosing reliable tools (like those built into exchanges) can help you avoid emotional trading, but there’s never such thing as “easy money.”

True wealth comes from sustained accumulation, not from fantasies of overnight riches. Calm down, take it step by step, and only then can you truly understand the market and yourself.