Hexun Investment Advisor Wu Yuying: A Path to Survival Through Quantitative Trading

This weekend, the topic of highest discussion wasn’t any particular sector, but rather the retail traders—because they collectively surrendered. No, you didn’t hear wrong, they really surrendered.

Liu Shahe wrote a book titled “Human Traders’ Quantitative Trading Surrender,” every word bloodstained. He said after practicing the market for over ten years, quantitative methods are completely useless; his account was halved, and he quit trading altogether. He’s not the only one—Xiao Fangshen lost 80 million yuan in half a month, and someone went from 800 million to just 200 million. Those familiar names have already disappeared from the Dragon and Tiger list. Some retail traders even said that once they made a move, they were immediately hit with the quantitative kill switch.

Why did retail traders lose so badly? Who shattered their livelihood? Ultimately, humans are completely powerless against advanced algorithms. Just as you try to trigger a limit-up, the machine instantly dumps chips to trap you; if the stock price fluctuates slightly, the machine sells unconditionally—no regard for broader strategy. The old ways of retail trading are now invalid.

With retail traders surrendering, is there still hope for individual investors? Yes. But you must abandon your previous short-term speculative mindset. Quantitative trading isn’t invincible; it has three fatal flaws. If you catch them, you can still survive.

First, quant models can’t handle low-liquidity, small-cap stocks because they need liquidity to harvest gains. Second, machines tend to run the same strategy repeatedly, causing a stampede effect during declines, which can crush truly valuable companies into golden pits. Third, you need to find situations where machines can’t predict—like running factories, analyzing trends, or truly understanding a company’s future—then you’ll have a chance.

So don’t be afraid. Liu Shahe’s surrender isn’t humanity’s failure. In the future, A-shares will reward those who focus on understanding companies, industries, and mid-term cycles, rather than those who race against machines.