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When Hot Money Starts Sending Exit Letters—The End of an Era and Retail Investors' Way Out
On March 16th, top liquidity trader Liu Shahe sat at his computer for a long time and wrote an article titled “The Human Trader’s Vectorized Trading Decree.”
This line was like a signal flare shot into the deep sea, instantly stirring waves across the investment circle.
“The tide of technology is vast and mighty; those who go with it prosper, those who oppose it perish. Today, after deep reflection, I realize human effort has its limits, but computing power is boundless.”
“With this document, I dedicate my trading terminals, strategy notes, and psychological logs—all surrendered, with no hope of saving them.”
“From now on, we lay down our swords and armor, and return to the fields.”
No longer the spirited enthusiasm of the past, only a profound sense of helplessness. The legendary figure who once traded from hundreds of thousands to billions, after cutting 3 million in late 2024 and angrily posting “Account Closure,” listed quantitative trading as one of the “Three Mountains.” Unexpectedly, a few months later, he chose a more tragic way—surrender.
Following him, N Zhou Tuesday, Huabei Ge, Beijing Traders, and other liquidity funds successively admitted defeat; rumors spread that Xiao Fang Shen lost 80 million in half a month, Zhang Mengzhu took a 20CM big loss, and Chen Xiaoqiun’s seat disappeared from the Dragon and Tiger list.
This collective “surrender” of liquidity funds became a symbolic sign of the transition in the short-term A-share trading world— the wealth arena of human traders is being ruthlessly ended by silicon-based algorithms.
They are not pretentious; they truly cannot beat them.
By the end of 2025, the scale of domestic quantitative private funds exceeded 2.5 trillion yuan. For every 100 yuan traded in A-shares, 30 yuan is contributed by quant strategies, especially higher in small-cap stocks. There are 128 private fund managers managing over 10 billion yuan in securities, of which 62 are quantitative managers—surpassing subjective long-only funds for the first time.
The arsenal of quantitative institutions is suffocating:
Milliseconds-level order placement—human speed is like static before algorithms
24-hour monitoring—emotionless execution, never tired
Supercomputing centers—extraction of over 10,000 trading factors
Microsecond data—everything from order book fluctuations to market news can be quantified
Liu Shahe plainly wrote in the decree: “The daring courage of the past has become bait for quantitative arbitrage; the emotional theories of yesteryear are now tools for machine harvesting.”
Data reveals the cold truth: in January this year, the average number of stocks held daily by liquidity departments was 72; by March, it dropped to 57. Only 15 stocks had more than 5 consecutive limit-ups, compared to 35 in Q4 last year.
Top liquidity funds face AI algorithms like generals in the era of cold weapons facing muskets—traditional methods of picking stocks, relay trading, and emotional betting are being crushed.
When the “cutting-edge” liquidity funds are bleeding heavily, what should retail investors do?
In fact, the brutality of the quantitative era is never limited to liquidity funds. Retail investors at the bottom of the market are also deeply trapped:
Despite Middle Eastern conflicts, tungsten prices keep rising, yet stocks are hammered worse than anyone else
Despite transformer orders surging, ZTE Electric drops four days in a row with big bearish lines
Despite energy shortages, nuclear concept stocks should be strong, but China Nuclear Construction opens low and declines
Even with fundamental understanding, the market is still harvested by quant strategies.
Where does quant profit come from? Industry data shows over 70% of gains come from retail investors cutting losses; 82% of retail investors only share 12% of profits, while a few institutions take over 35%.
Market scams are normalized: high-frequency order placements and cancellations, fake orders, manipulative pushes, false breakouts, sudden drops after诱多 or诱空, chasing涨必套, bottom-fishing buried.
Retail investors’ opponents are no longer emotional human traders but a group of 24/7 AI machines reacting in milliseconds.
If you don’t want to be precisely targeted by quant algorithms as a “leek,” these four principles must be ingrained in your mind:
First, extend your investment horizon and abandon high-frequency trading.
Quant profits come from high-frequency trades, but if you hold your stocks steady, they can’t find targets to harvest. Lengthening your holding period avoids 90% of the harvesting zones. Data shows that retail investors holding stocks over a year have over four times the profit probability of ultra-short-term traders.
Second, maintain high cash flow and high-yield assets.
Seek high-dividend stocks and use stable dividends as a safety net. When stock prices fall, dividend yields rise, and key price levels often see strong long-term support from big funds. This value floor, supported by real money, is difficult for quant models to break through.
Third, stay away from small-cap “monster stocks” and hold onto the big market giants.
Quant strategies excel at harvesting volatile, small-cap stocks, but struggle with trillion-market-cap blue chips like banks and energy companies.
Fourth, learn to recognize quant footprints and use them in reverse.
Shanghai Qianbo Asset’s General Manager Shu Qiquan points out the importance of observing order book anomalies and understanding “dumping V-reversal” features of quant accumulation. At such times, not only should you avoid止损, but also see it as an opportunity. Abandon high-speed battles with quant algorithms; shift to swing trading and logic-driven strategies. Deeply explore sectors like new stocks, restructuring, and niche themes where quant coverage is weak.
The “collective surrender” of liquidity giants marks the end of an era. It signals that the era of “human brain” driven ultra-short-term speculation is fading, and the era of “silicon-based” algorithmic trading has fully arrived.
But as “folk stock god” Lin Yuan said: “AI can process data but cannot understand human nature; quant can track trends but cannot judge the ultimate value of a business model.”
The core of investing has never been about who can calculate faster, but who sees more accurately, far-sightedly, and understands deeper. Machines have no emotions, no common sense, and no industry lifecycle experience. They can profit from volatility but struggle with growth; they can make quick money but find it hard to generate compound returns.
As ordinary retail investors, we cannot change the rules, but we can choose to adapt.
Abandon unrealistic fantasies of quick wealth, lower expectations, and return to rationality and value. In this brutal and efficient market, survival is more important than anything else.