On July 25, 2026, the Private Securities Investment Fund Professional Committee of the Asset Management Association of China (AMAC) gave an interview to Yicai, offering a comprehensive explanation of quantitative trading in A-shares, covering fairness, trading volume, market impact, rules, and regulatory measures. The committee denied that quantitative trading enjoys "T+0" privileges, rejected claims of "coordinated selling," and asserted that current regulations are sufficiently strict. However, these positions show clear contradictions with extensive market data, academic research, and regulatory practices. This article provides a detailed, point-by-point analysis.
Claim 1: "Quantitative Trading Has No T+0 Privilege": Institutional Fairness Does Not Equal Substantive Fairness
The committee's core argument is: "The current trading rules of the exchange treat all investors fairly. Regardless of the type of investor, only T+1 trading is permitted in the stock market, and quantitative trading investors are no exception."
This defense confuses "institutional fairness" with "substantive fairness."
The committee acknowledges that investors can achieve so-called "T+0" trading by holding a stock on day T-1, buying it on day T, and then selling the day T-1 holdings. The problem lies in the execution: quantitative institutions, using algorithms and programmatic order placement, can complete this operation in milliseconds. In contrast, retail investors, relying on manual monitoring and order placement, operate at a completely different level of speed and information processing.
Market participants have directly stated: "The root cause of retail investors' deep resentment is the institutional inequality—quantitative firms can place orders milliseconds faster than retail investors and use existing holdings to execute virtual intraday T+0 trades, profiting from volatility. Meanwhile, retail investors are restricted to T+1, lacking a timely correction mechanism." Under the same set of rules, the actual outcome is vastly different for those with technological advantages versus those without. Using "identical rules" to address "substantive unfairness" is a classic case of evasion.
Prominent scholar Professor Liu JiPeng has pointed out: "Leveraging their advantages in 'speed of information' and 'speed of action,' quantitative institutions use high-frequency order placement and cancellation to create 'Type-A' stock price patterns—sharp rises and falls within days—causing retail investors who follow the trend to be repeatedly 'harvested'."
Institutional fairness cannot replace outcome fairness. Regulators restrict mutual funds from engaging in intraday reverse trades on the same stock specifically to prevent those with capital advantages from profiting in this way. Quantitative funds, possessing both capital and technological advantages, should face even stricter restrictions on such intraday reverse trading. In the A-share market, where retail investors dominate, the competition between quantitative institutions and retail investors is essentially a "computer versus flesh and blood" mismatch.
Claim 2: "Quantitative Trading Did Not Cause Coordinated Selling": Sample Bias and Logical Flaws
The committee stated: "According to information from leading brokerages and quantitative private funds, on the trading days last week with significant market declines, many quantitative institutions were net buyers, not net sellers." It also said that "domestic mainstream quantitative products, primarily index enhancement, quantitative long-only, and quantitative neutral strategies, maintain over 90% high position levels year-round."
This conclusion suffers from severe sample bias and logical flaws.
First, the committee's data source is self-reports from "leading brokerages and quantitative private funds." The objectivity of asking the investigated subjects to self-report whether they engaged in "selling pressure" is inherently questionable. Furthermore, quantitative trading behavior is decentralized and systematic, not a "unified, coordinated sell-off"—but decentralized selling can still create a combined selling force.
Second, "high positions" do not prove an absence of selling pressure. Quantitative institutions can easily conduct large-scale portfolio rebalancing while maintaining high positions—selling stock A while buying stock B. For the overall market, this still represents selling pressure. In 2024, a quantitative private fund was fined by the exchange for selling 1.372 billion yuan of Shenzhen-listed stocks within 42 seconds of the market opening and 1.195 billion yuan of Shanghai-listed stocks within one minute. Selling nearly 1.4 billion yuan in 42 seconds—if that isn't "coordinated selling," what is?
Third, academic research provides contradictory evidence. One study, based on data from January to September 2023, indicates that "quantitative trading has a significant impact on the stock market, including a certain degree of 'selling pressure' effect." Another study points out that "quantitative trading, by crowding out informed traders and short sellers, slows the market's absorption of new information, reducing information efficiency." Quantitative trading is not the market "stabilizer" the committee portrays.
Claim 3: "Regulation is Stricter than Overseas Markets": Selective Comparison and Factual Distortion
The committee claimed: "The U.S. SEC and exchanges do not have rigid regulations like '15 orders per second, 15% cancellation rate, 50-millisecond order lifespan,'" and argued that "A-share regulatory constraints on quantitative trading are significantly stricter than those in overseas markets." They cited a 50% order cancellation monitoring threshold in A-shares compared to 90% in the U.S. and 70% in Japan as an example.
This argument has multiple problems.
First, the committee's statement about the U.S. "15 orders per second" rule contradicts a large amount of publicly available information. Multiple sources indicate that the U.S. SEC clearly identifies submitting more than 15 orders per second as high-frequency trading, a rigid monitoring red line. Once triggered, exchanges and the SEC will focus their monitoring on the entity. Although this might not be a "hard prohibition" in legal statutes, its binding force as a regulatory red line cannot be denied. The committee's use of "no rigid regulation" to downplay the regulatory gap between China and the U.S. is misleading.
Second, the claim that the A-share standard of 300 orders per second is stricter than the U.S. standard is unfounded. In reality, the A-share high-frequency identification standard is closer to "filing monitoring" than a "rigid constraint"—exceeding the standard merely triggers classification for differentiated regulation, not a direct ban. In contrast, the intensity of regulation and the severity of penalties for high-frequency trading in the U.S. are much stricter.
Third, the comparison of cancellation rates is an outright bait-and-switch. In the U.S., a daily order cancellation rate exceeding 15% can trigger a review or punitive fees. In China, the 50% monitoring threshold is merely an "abnormal monitoring" indicator. The regulatory effect of the two is completely incomparable. Using a "monitoring indicator" to compare with a "punitive threshold" to conclude that China is "stricter than overseas" is entirely unconvincing.
Claim 4: "Quantitative Trading Improves Liquidity": Positive Effects Cannot Mask Negative Effects
The committee stated that quantitative trading "can narrow bid-ask spreads, reduce transaction costs for all market participants, and broaden market depth." It is true that quantitative trading has improved market liquidity to some extent. However, this positive effect cannot overshadow the structural problems it creates.
The key point is: the A-share market is dominated by retail investors, while in mature overseas markets, quantitative trading often faces other institutions as counterparts. The same quantitative trading strategy can produce entirely different effects in different market structures. Overseas retail investors have access to various risk-hedging tools, while A-share retail investors lack effective hedging instruments. In a zero-sum game pattern, insufficient incremental capital is the market's fundamental problem—quantitative trading merely uses its technological edge to take a larger slice of the existing pie without enlarging the pie itself.
A significant portion of quantitative trading in the U.S. market involves arbitrage and hedging, unlike the directional trading prevalent in A-shares. The market impact of directional trading is not comparable to that of hedging and arbitrage trading. By directly comparing these two fundamentally different types of quantitative trading, the AMAC committee commits an error in the type of comparison.
Furthermore, academic research has revealed the "double-edged sword" effect of quantitative trading: while algorithmic trading improves market liquidity and suppresses price volatility, it also "slows the market's absorption of new information, reducing information efficiency." The committee's focus only on the positive aspects, while ignoring the negative, represents a selective narrative.
The Inherent Limitations of Industry Self-Defense
As a self-regulatory body for the fund industry, the AMAC Private Fund Committee's members themselves come from the industry. For industry stakeholders to respond to industry controversies naturally limits the objectivity of their views.
In fact, the regulators themselves have been more cautious in their stance than the committee's statements. During the 2026 National People's Congress and Chinese People's Political Consultative Conference sessions, CSRC Chairman Wu Qing clearly stated the need to "highlight the principle of fairness and deepen and refine the regulation of high-frequency quantitative trading." At investor symposiums, he further emphasized "resolutely maintaining an open, fair, and just market order." The shift in phrasing from "standardized development" to "standardized behavior" suggests that more specific policies are on the way.
In summary, quantitative trading has evolved alongside the development of the capital market. However, this does not mean the current model requires no adjustments. The core of the issue is not whether to have quantitative trading, but how to ensure that technological advantages do not evolve into institutional unfairness in a market dominated by retail investors. Avoiding the issue and downplaying the controversy will not help build a truly fair market ecosystem.
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