# Retail Investors Trapped in Algorithmic Hunt, Veteran Investors Forced to Write "Surrender Letters"? "Anti-Quantitative Guide" Suddenly Goes Viral, Private Equity Mogul Dan Bin Discusses the Only Way to Beat Quantitative Trading

How Should Ordinary Investors Adjust Their Strategies to Respond to Quantitative Challenges?

Recently, the A-share market has continued to adjust, and quantitative funds have once again become the focus of public discussion. A sudden trend of “Anti-Quantitative Harvesting Strategies” went viral in the private equity circle over the weekend, sparking widespread debate.

Currently, the trading ecosystem of A-shares is continuously evolving. Thanks to its high frequency, high precision, and homogeneity, quantitative trading has shifted from a supporting role to a mainstream market force. Today, ordinary investors face not only human emotions but also 24-hour AI machines as trading opponents.

This shift has changed the logic of A-share trading. The success rate of traditional short-term strategies for ordinary investors has significantly declined, leaving them trapped in the “hunting” of quantitative algorithms. Even seasoned investors like “Stock Enthusiast Liu Shahe” have helplessly written “A Human Trader’s Guide to Quantitative Trading.” So, in a market dominated by quantitative trading, how can ordinary investors avoid being harvested?

Quantitative Hunting in A-shares

Veteran Investors Frustrated and Writings of “Guidance”

The ongoing transformation of the A-share trading ecosystem has profoundly impacted market participants. Quantitative trading, with its efficient data analysis, precise execution speed, and homogeneous operation mode, has rapidly risen and completely reshaped the trading environment. Ordinary investors, who are at a natural disadvantage in information access, analysis speed, and execution, see their traditional short-term strategies’ success rates plummet, falling into the trap of precise quantitative algorithms.

As this trend intensifies, the proportion of quantitative trading in the entire market continues to increase. Its presence is especially prominent in small-cap stocks, micro-cap stocks, and popular themes.

Data shows that the number of private equity funds with over 100 billion yuan in assets under management has surpassed those with subjective strategies of similar size. Leading quantitative institutions have dedicated supercomputing centers and can analyze over 10,000 trading factors—from market news and investor trading habits to individual stock genetic traits and order book changes—forming a large-scale, systematic trading framework.

The core operations of quantitative trading hit the weaknesses of ordinary investors’ trading behaviors, causing traditional retail strategies to repeatedly fail. A seasoned investor lamented on social media: “Logic no longer works; tungsten prices keep rising, but tungsten stocks in the market are falling worse than anyone; transformer orders explode, but Tebian Electric (TBEA) has fallen for four consecutive days with large declines; nuclear power stocks, which looked great over the weekend, opened lower and continued to decline. Technical analysis can’t beat quant, and even fundamental logic, when applied to the market, still faces trading method issues.”

Notably, veteran investor “Stock Enthusiast Liu Shahe” even wrote “A Human Trader’s Guide to Quantitative Trading,” reflecting the passive position of ordinary investors in the game against quant algorithms and highlighting the profound impact of quantitative trading on the A-share trading ecosystem.

Beware of Human Nature Dislocation

Return to the Essence of Value Investing

Quantitative trading has made the A-share market more professional and brutal, forcing ordinary investors to abandon speculative short-term thinking and return to the essence of value investing.

Chen Xinwen from Heizi Capital told reporters that liquidity crises are essentially indiscriminate sell-offs, but value reversion will eventually occur. When quantitative models based on volatility control reduce positions passively, and fundamental factors temporarily fail, high-quality assets may experience irrational discounts—precisely the window for long-term capital deployment. However, Bin warned that “collapse” should be understood more as a deep concern about crowded strategies and regulatory lag.

Data shows that by the end of 2025, the scale of domestic quantitative private equity funds will have exceeded 1.8 trillion yuan, accounting for over 30% of private equity securities funds, with market influence becoming significant. Chen Xinwen pointed out that quantitative reduction is not based on company value judgments but is a mechanical execution of risk budgets. This means that even fundamentally sound blue-chip stocks are not immune in systemic deleveraging.

Chen Xinwen emphasized that what we should truly be wary of is never the quantitative technology itself but the dislocation of human greed and risk perception—when everyone embraces the “algorithmic Holy Grail,” it may be time to return to subjective research and valuation. The market always rewards those who penetrate noise and adhere to common sense over the long term, and this confidence is what allows us to navigate cycles.

Private equity leader Dan Bin previously stated clearly, “The only way to beat quant is through value investing.”

Five Major Strategies for Ordinary Investors to Avoid Quantitative Harvesting

Breaking Through Quantitative Harvesting

For ordinary investors, the “onslaught” of quantitative trading presents multiple practical challenges. However, in a market dominated by quant, there are still ways to navigate. The key is to abandon traditional methods, adapt to quant logic, adhere to principles that oppose human nature, avoid套路 (套路: routines or tricks), think long-term, and maintain strong discipline—learning to “dance with” quant algorithms. Industry experts suggest that, by aligning trading strategies with the characteristics of quantitative trading, investors can make adjustments in five key areas.

1. Focus on medium- to long-term positioning, abandoning high-frequency trading. Quantitative profits mainly come from intraday and short-term volatility, but ordinary investors should prioritize trends and fundamentals, extend holding periods, and avoid the 90% of quant harvesting zones. Data shows that retail investors holding stocks for over a year have a profit probability more than four times higher than short-term traders. Select stocks with solid fundamentals and clear logic, reduce monitoring frequency, and hold long-term to escape the short-term game of quant.

2. Avoid “hot zones” heavily targeted by quant, and choose quality stocks. Quantitative trading dominates in micro-cap stocks, stocks with no earnings, and stocks with continuous high openings. Ordinary investors should steer clear of these and instead select large-cap blue chips, industry leaders, stocks with confirmed earnings, and those heavily held by institutions. These stocks have large market caps, solid fundamentals, and are less susceptible to control by quant institutions, with prices more aligned with intrinsic value, helping to smooth market volatility.

3. Develop anti-quant behaviors and establish fixed trading rules. Quantitative institutions love to harvest retail investors’ chasing highs, panic selling, and heavy positions. Therefore, investors should avoid chasing highs, panic selling, or going all-in; instead, adopt staggered buying and selling, set strict stop-loss and take-profit levels, and enforce discipline to prevent human weaknesses from triggering algorithmic traps.

4. Use “institutional thinking” instead of “retail intuition,” and reduce market noise. Abandon retail habits like watching order books and guessing short-term moves; focus on core fundamentals such as company performance, cash flow, and sector outlook. Operate with a “right-side” low-buy strategy, avoid active quant trading in the early session, and consider using index funds or sector ETFs to diversify and smooth volatility, locking in market Beta returns.

5. Reduce trading frequency and improve win rates. High-frequency trading is an advantage for quant but a disadvantage for retail investors. Keep weekly trading to once or less, which significantly increases success rates. Focus on a few high-quality stocks, buy when prices dip to previous lows, and take profits near previous highs. Instead of competing with quant on short-term price differences, grasp medium-term price fluctuations—“don’t trade just for the sake of trading; wait for the right moment, even go to zero or hold cash, and act decisively when the time comes.”

｜Daily Economic News nbdnews Original Article｜

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