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 started to emerge in the market, pointing the finger at quantitative trading—“If not quantitative harvesting, then who else could it be?”

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 private securities funds, nearly doubling from 650 in January this year, a 99.38% increase, hitting a two-year high.

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

Even more noteworthy is that the number of billion-yuan quant private funds has surpassed that of billion-yuan 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 domestic quant private fund scale exceeded 1.8 trillion yuan, accounting for over 30% of private 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 for public funds tracking the CSI 300, CSI 500, and CSI 1000 indices were 3.9%, 4.88%, and 11.06%, respectively; private funds showed even higher returns. The Chaoyang Evergreen segmented strategy index indicated that during the same period, the annualized excess returns for quantitative products tracking the CSI 300, CSI 500, and CSI 1000 were 6.61%, 8.81%, and 18.58%. The CSI 2000 index, established later, had better annual excess returns than the CSI 1000 during the same period. Since 2024, public and private funds tracking the CSI 2000 have achieved annualized excess returns of 8.93% and 15.96%, respectively.

Small Caps: 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.

A researcher from a public fund told reporters, “Small caps 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 quant 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 gains, and add positions on stocks with large short-term selling pressure and undervaluation. By frequently buying low and selling high in small increments, they accumulate small profits that, over time, generate a relatively stable compound effect.

“People who buy small caps want to profit from price fluctuations,” said the public fund researcher. “Because the value center of small caps remains relatively stable over the long term, valuation sometimes becomes ineffective. The market is more driven by trading sentiment and momentum. In such an environment, the speed and data processing advantages of quant come into play. It’s not about prediction but about capturing short-term pricing deviations. How can humans compete with machines?”

Retail Investors’ Losses from Panic, Quantitative Strategies Exploit Short-Term Deviations

Regarding the claim that “quantitative strategies are 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 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,” said the private fund manager. “Quantitative trading has advantages in 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 their roles: ‘You chase highs and sell lows, I provide liquidity; others discover value.’ That’s how the market operates.”

He likened quant trading to a sprinter constantly sprinting, passing the baton, and sprinting again; while subjective long-only investors are marathon runners, slowly holding a stock. 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, while quant funds buy at those lows; retail investors chase highs, and quant funds 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 do the work for you; or you can stick to what you’re good at—value investing and profiting from corporate growth.”

Different tracks always have different runners.

Daily Economic News