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On April 3, 2025, the three major exchanges released the &#34;Implementation Rules for Programmatic Trading Management,&#34; which officially took effect on July 7 of last year. By April 3, 2026, it will have been one year since the implementation rules were published by the Shanghai, Shenzhen, and Beijing exchanges.
In the &#34;Implementation Rules,&#34; if an investor's trading behavior involves a single account making more than 300 declarations or cancellations per second, or more than 20,000 declarations or cancellations in a single day, it is classified as high-frequency trading. Additionally, abnormal trading behaviors are detailed, and differentiated supervision is implemented, particularly through differentiated fee arrangements to increase trading costs.
One year after the release of the new regulations on quantitative trading, has high-frequency quantitative trading been effectively controlled?
Among the data worth our attention is a set of figures.
According to publicly available data, as of the first quarter of this year, the domestic quantitative camp with over 10 billion yuan in assets has expanded to 61 firms, with the overall management scale approaching 2 trillion yuan. In terms of management scale, it is currently close to 2 trillion yuan, having increased by nearly 400 billion yuan compared to the end of last year’s fourth quarter, and showing a significant year-on-year increase of about 800 billion yuan.
From the perspective of the investment scale of leading quantitative institutions, several top quantitative firms have entered the tier of over 80 billion yuan in investment scale, just one step away from the 100 billion yuan investment scale.
On one hand, the investment management scale of leading quantitative institutions is growing larger, while on the other hand, the pace of survival of small and medium-sized quantitative institutions is accelerating, resulting in a clear Matthew effect in the entire industry.
Leading quantitative trading institutions continue to achieve excess investment returns, leveraging AI, big data, and other methods to gain sustained investment advantages in the stock market, thereby increasing the difficulty for retail investors to make profits, which is something retail investors have felt most deeply in recent years.
The stock market is essentially a place for wealth redistribution. If institutions achieve excess returns in the stock market, it means that some investors will incur losses in the market.
High-frequency quantitative trading in the A-share market is highly controversial, with investors focusing on the criteria for identifying high-frequency trading itself and the penalties for high-frequency abnormal trading and violations.
Under the influence of the new regulations on quantitative trading, if a single account makes more than 300 declarations or cancellations per second, it is classified as high-frequency trading. However, how to classify trading behaviors that involve a single account making 299 declarations or cancellations per second is undoubtedly a concern for the market.
Quantitative trading has only been developing in the A-share market for about 10 years, with explosive growth occurring roughly after 2020.
In contrast, quantitative trading has been present in the European and American stock markets for several decades, currently contributing over 80% of the liquidity in local markets, and its impact on local markets cannot be underestimated
How is high-frequency quantitative trading regulated in the US and European stock markets?
Taking the US stock market as an example, the regulation of quantitative trading primarily focuses on whether such trading activities may mislead the market.
In practice, common violations in high-frequency quantitative trading include false orders, layered inducement, front-running, and market manipulation. Quantitative trading firms utilize algorithms, customer order information, and multi-layered orders to achieve arbitrage. Any issues related to inducement trading or misleading the market will face severe penalties.
In terms of penalties, the consequences can range from hefty fines and confiscation of illegal gains to lifetime bans from the industry and criminal charges, with responsible individuals facing imprisonment.
In the European market, regulators pay more attention to abnormal trading behaviors, price manipulation, and the provision of false liquidity in relation to high-frequency trading.
The regulatory actions against high-frequency quantitative trading in Europe have significantly increased the costs of ineffective high-frequency trading. Once behaviors such as false trading or price manipulation are detected, firms will face substantial penalties and criminal liability. For quantitative trading firms, every trading action must be approached with extreme caution.
Overall, the regulatory focus of the US and European stock markets on high-frequency quantitative trading does not overly emphasize the frequency itself but rather whether high-frequency trading leads to market misguidance.
Currently, quantitative trading provides substantial liquidity to the US and European stock markets, but there are concerns regarding the authenticity of this liquidity. If quantitative trading firms provide false liquidity to the market through deceptive or inducement trading, resulting in market misguidance, such trading behaviors will face very severe penalties.
Compared to the A-share market, the trading rules in the US and European stock markets appear to be more comprehensive.
For instance, there are no price limits in the US and European stock markets, and T+0 trading is allowed across the market, providing both individual and institutional investors with multiple opportunities to correct errors. Additionally, for retail investors, risk hedging tools are more abundant, meeting the needs for intraday risk hedging.
In this context, even though quantitative trading firms may leverage algorithms and AI to gain a competitive advantage, the overall market's T+0 trading and comprehensive risk hedging tools significantly increase the trading costs for quantitative firms.
Crucially, the institutionalization level in the US and European markets exceeds 80%, while the A-share market remains predominantly retail-driven. This means that quantitative firms can use AI and algorithms to simulate retail trading behaviors, becoming counterparties to retail investors. Retail investors cannot compete with quantitative trading firms equipped with powerful technical tools, naturally placing them at a disadvantage in the stock market.
Globally, quantitative trading primarily plays the role of providing market liquidity and acting as market makers in major stock markets. However, in the A-share market, quantitative trading excels at capturing retail investors' trading behaviors and is more likely to view retail investors as counterparties. Analyzing from a certain perspective, the main impact of domestic quantitative trading is not only to provide liquidity to the market but also to capture retail investors' trading behaviors and investment sentiments for arbitrage. This is also the primary reason why quantitative trading has continued to be profitable in recent years while retail investors have struggled to make money
How to standardize high-frequency quantitative trading behavior?
For the A-share market, standardizing quantitative trading behavior primarily hinges on significantly increasing the difficulty of capturing retail investors' trading actions and investment sentiments. The most direct approach is to relax T+0 trading across the entire market while providing retail investors with more risk hedging tools.
In practical operations, to prevent excessive speculative behavior in the market, the number of T+0 trades can be appropriately limited. For example, retail investors should not exceed 2 intraday trades. Additionally, for retail investors, it is necessary to pass a professional test, achieving a score of 80 or above, in order to access more risk hedging tools.
Only by greatly increasing the difficulty for quantitative institutions to capture retail trading behaviors and sentiments can we maintain the fairness of retail investors' trading in the stock market. The phenomenon of &#34;quantitative trading continuously earning excess returns while retail investors cannot make money&#34; can fundamentally change

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On April 3, 2025, the three major exchanges issued the "Implementation Rules for Programmatic Trading Management," which officially took effect on July 7 of last year. By April 3, 2026, the implementation rules for the Shanghai, Shenzhen, and Beijing exchanges will have been in effect for one year. The new regulations classify behaviors where a single account submits or cancels more than 300 orders per second or exceeds 20,000 orders in a single day as high-frequency trading, and will implement differentiated supervision and fees. Despite the regulation of high-frequency quantitative trading, the number of domestic quantitative institutions managing over 10 billion has increased to 61, with a management scale approaching 2 trillion yuan, reflecting the Matthew effect in the industry, where leading institutions continue to achieve excess returns, while retail investors face greater challenges

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One year after the release of new regulations on quantitative trading, how do European and American markets regulate high-frequency quantitative trading?