Buy when it drops, sell when it rises! Why has your panic become prey for quantitative traders?

“Clearly, I like a stock, but as soon as I buy, it drops; I panic and sell, and it rises.” This has been the most direct experience for many retail investors this year.

Meanwhile, a voice has begun to emerge in the market, pointing the finger at quantitative trading—“If not quantitative trading, then who is harvesting?”

Rapid Expansion of Quant Funds

The reason why quantitative trading has attracted so much attention is closely related to the rapid growth of quant funds in recent years.

Wind data shows that by February 2026, there were as many as 1,296 registered securities private funds, nearly doubling from the 650 registered in January this year, a 99.38% increase, hitting a two-year high.

Further data indicates that as of March 19, 2026, a total of 2,878 securities private funds had completed registration this year, a more than 60% increase compared to 1,786 in the same period last year.

More notably, the number of billion-yuan quant private funds has surpassed that of subjective strategy private funds for the first time. There are 126 domestic private fund managers managing over 100 billion yuan, with quant funds accounting for half. By the end of 2025, the scale of domestic quant private funds had exceeded 1.8 trillion yuan, accounting for over 30% of private equity securities funds.

Behind the registration surge are impressive performance results. In a previous report, Orient Securities pointed out that from January 1, 2018, to December 31, 2025: the average annual excess returns of public funds tracking the CSI 300 index (enhanced index funds), CSI 500, and CSI 1000 were 3.9%, 4.88%, and 11.06%, respectively; private funds showed even higher returns. The Chaoyang Evergreen Strategy Index indicated that during the same period, the annualized excess returns of quantitative products tracking the CSI 300, CSI 500, and CSI 1000 were 6.61%, 8.81%, and 18.58%. The CSI 2000 index, which was established later, also outperformed the CSI 1000 in annual excess returns. Since 2024, public and private funds tracking the CSI 2000 have achieved annualized excess returns of 8.93% and 15.96%, respectively.

Small-cap Stocks: The Hunting Ground for Quant

It is well known that existing market quantitative strategies favor small-cap stocks, which are related to their unique trading structures: low institutional participation, mainly individual investors, and highly irrational trading behaviors, leaving significant room for contrarian investing.

Wang Ying, Deputy Director of Quantitative Investment at CITIC Prudential Fund and Fund Manager, pointed out that small micro-cap stocks with a market value around 2.5 billion yuan are difficult for mainstream institutional investors to include in their core stock pools, and research coverage from sell-side analysts is limited. Their trading counterparts are mostly individual investors with diverse behavioral patterns.

An investment researcher from a public fund told reporters, “Small-cap stocks are indeed less correlated with fundamentals. Many small-cap companies are overvalued, mainly supported by liquidity.”

In the view of this researcher, this liquidity-driven market pattern provides a natural environment for quantitative strategies to thrive.

Quant models based on factors such as individual stock capital flows, trading data, and price-volume performance can quickly lock in gains on targets with inflows and significant appreciation, while adding positions on stocks with large short-term selling pressure and undervaluation due to market mispricing. By frequently executing small buy and sell trades, accumulating small profits per trade, they can generate a relatively stable compound effect over time.

“People who buy small-cap stocks want to profit from price fluctuations,” said the public fund researcher. “Because the valuation center of small stocks remains relatively stable over the long term, sometimes valuation metrics become ineffective, and the market is more driven by trading sentiment and momentum. In such an environment, the speed and data processing advantages of quant strategies come into play. They do not rely on prediction but on capturing short-term pricing deviations. How can humans compete with machines?”

Retail Investors’ Losses Come from Panic; Quant Strategies Exploit Short-term Price Deviations

Regarding the claim that “quantitative trading is harvesting retail investors,” a subjective long-only private fund manager offered a different perspective. He gave an example:

Suppose a retail investor expects a stock to rise from 10 yuan to 20 yuan and buys in. But the next day, the stock opens lower, and the investor, panicking, sells at 9 yuan. This selling causes the stock price to deviate from its mean in the short term. The quant model detects this deviation and takes the position at 9 yuan, selling when the price rebounds to 9.5 yuan. In the end, the retail investor loses 1 yuan, while the quant strategy gains 0.5 yuan.

“Retail investors lose because of panic trading, and quant strategies just exploit short-term market deviations. It’s not about who is harvesting whom; it’s about differences in trading behavior,” the private fund manager said. “Quantitative strategies have advantages in trading technology and model building compared to ordinary investors, which is a fact. Currently, there are clear regulatory policies against abnormal trading, and big data monitoring is strict. All market participants play a role—‘you chase highs and sell lows, I provide liquidity, and others discover value.’ That’s how the market operates.”

He likened quant strategies to sprinters who keep rushing, relaying, and sprinting again; while subjective long-only investors are like marathon runners, slowly holding onto stocks. Clients choose whether to sprint or jog based on their preferences, each doing what they excel at.

Returning to the initial question: Why do retail investors always feel targeted by quant strategies?

The answer is simple: because their trading behaviors happen to trigger the algorithms. Retail investors panic and sell at lows; quant strategies buy at those lows. Retail investors chase highs in euphoria; quant strategies distribute at highs. Essentially, it’s a race of speed, and machines are indeed faster.

As the private fund manager said, this doesn’t mean retail investors can only be harvested. “Either you can’t beat them and join them—let quant strategies do the work for you; or you stick to what you’re good at—value investing and earning from corporate growth.”

Different tracks have different runners.

Daily Economic News