Summary of Key Points
This article discusses the question of whether quantitative trading is the primary cause of retail investors' losses. By combining expert opinions, regulatory actions, and market data, it concludes that quantitative trading is not the main reason for retail investors' losses. Its essence represents a advancement in trading technology; however, the "asymmetry in speed" it creates can lead to unfairness. Retail investors' long-term losses are more often due to their own behavioral biases (such as chasing gains and cutting losses) and differences in the market environment. The regulatory focus is on regulating quantitative trading rather than suppressing it, with the aim of eliminating these unfair speed advantages. The best strategy for retail investors is not to compete against machines but to avoid short-term speculation through indirect investments (such as pensions and index funds) and to overcome their own psychological weaknesses.
I. Quantitative Trading: The Scapegoat for Retail Investors' Losses?
Many people attribute retail investors' losses to quantitative trading, but experts have different views:
- Wu Xiaoqiu (former vice president of Renmin University of China): Quantitative trading is merely a change in trading technology, and there is no evidence that it causes retail investors' losses. The key is to regulate it under fair rules.
- Li Xunlei (chief executive of CITIC International): We need to view quantitative trading dialectically; eliminating it will not necessarily improve the stock market.
- Liu Jipeng (professor at China University of Political Science and Law): He opposes sacrificing the fairness of 95% of retail investors for the efficiency of 5% of institutional investors.
In fact, retail investors were losing money even before quantitative trading emerged—previously, it was large traders, speculative funds, and those with insider information who exploited them. Quantitative trading has just become a new "tool" for profit-taking, but the root cause lies in the unfair ways it is used (such as its speed advantage).
II. Regulatory Action: Has Quantitative Trading's "Speed Advantage" Been Eliminated?
In July 2026, the Shanghai Stock Exchange shut down the dedicated lines in its data centers (which only institutional investors could use to access market data), and the Shenzhen Stock Exchange followed suit, ensuring that all institutions are on an equal footing physically.
- Previous advantage: These dedicated lines provided a speed advantage of tens to hundreds of milliseconds over ordinary investors (1 second = 1000 milliseconds; a blink of an eye is about 400,000 microseconds). High-frequency trading took advantage of this speed difference, similar to using a nuclear weapon against a spear.
- Institutional responses: Unable to use their own data centers, institutions moved to third-party facilities near the stock exchanges (for example, cabinets within 3 kilometers of the Shanghai Stock Exchange's Jinqiao Data Center), with rent increases of 50% or even doubling. They also purchased higher-grade dedicated lines to further optimize their networks and continue to pursue faster speeds.
- Regulatory purpose: The goal is not to suppress quantitative trading but to regulate it, encouraging a shift from high-frequency strategies that rely on speed to medium- and low-frequency strategies based on models and fundamentals.
III. Don't Confuse: Quantitative Trading, Programmatic Trading, and High-Frequency Trading Are Not the Same
Many people use these terms interchangeably, but there are significant differences:
- Quantitative trading: It is an "investment method" that uses mathematical models to replace human decision-making, such as defining rules for "low valuation + high growth" to identify stocks for investment.
- Programmatic trading: It is a "trading tool" that uses computers to place orders automatically; it does not necessarily involve quantitative analysis (for example, manually selecting stocks and then using a program to buy them).
- High-frequency trading: It is an extreme form of programmatic trading where positions are held for fractions of a second, with tens of thousands of orders placed and canceled in a day, aiming to earn small profits (e.g., 0.1% per trade, resulting in a profit of 100 yuan from ten thousand trades).
New regulations defined in July 2025 state that trading more than 300 orders per second or more than 20,000 orders in a day constitutes high-frequency trading, which is the focus of regulatory oversight.
IV. Retail Investors Always Lose Money: The Root Cause Lies with Them, Not Quantitative Trading
Data speaks for itself:
- In 2025, 80% of retail investors lost money, with an average loss of 20,000 yuan per investor. During bear markets in 2018 and 2022, the loss rate exceeded 85%, and even during the bull market from 2019 to 2020, 60% of retail investors lost money.
- In the long run, retail investors lose because of behavioral biases (chasing gains and cutting losses) and disadvantages related to the tools they use (lack of speed and advanced models compared to quantitative trading).
Comparison with the United States:
- Although there is more quantitative trading in the U.S., ordinary investors benefit from indirect investments such as pensions and index funds, which earn profits from companies' growth. The turnover rate is lower, allowing them to benefit from the stock market's long-term growth.
- U.S. reports show that retail investors underperform the market mainly due to their frequent trading, which has little to do with the level of quantitative trading.
V. What's the Future? Fair Rules + the Right Approach for Retail Investors
- Regulatory direction: The China Securities Regulatory Commission is committed to improving the regulation of programmatic trading and cracking down on market manipulation and the abuse of technical advantages to maintain fairness.
- Retail investors' strategies:
1. Don't try to compete with machines in terms of speed—quantitative trading can execute hundreds of trades per second, so manual trading is outclassed.
2. Use indirect investments, such as pensions and proven funds (like index funds), to participate in the market and earn long-term growth rather than engage in short-term speculation.
3. Overcome your own behavioral flaws—avoid chasing gains and cutting losses, as this is more important than trying to outperform machines.
In conclusion, quantitative trading is neither a demon nor a scapegoat. The future of the market lies in fair rules and retail investors recognizing their limits and stepping out of the "zero-sum game" mentality.
Disclaimer: This article is an objective analysis and does not constitute investment advice.