Quantifying "Crime and Punishment": Blame it for the declines, but what about when the market rises?
The A-share market has experienced dramatic volatility recently. On July 1, the Shanghai Composite Index opened at 4090.76 points and closed at 4112.45 points. On July 20, it closed at 3796.28 points, marking a cumulative decline of over 7.28% for the index in this interval. Among these dates, the Shanghai Composite Index saw its largest drop on July 17, falling 3.05% that day and breaking below the annual moving average. During the week from July 13 to July 17, the Science and Technology Innovation 50 Index plummeted 16.93%, and the ChiNext Index fell 11.94%, with the growth track suffering an even more severe sell-off. Against the backdrop of no systematic negative factors in fundamentals and macro liquidity remaining reasonably abundant, the continuous decline of indices and sustained pressure on trading accounts have pushed market sentiment to a critical game-theory window. Almost simultaneously, public opinion has targeted a specific target — quantitative trading.
From severe denunciations of "asymmetric harvesting" by some academic figures, to public questioning of "emotion factors" by a director of investor relations at a listed company on their social media feed, and to complaints from some individual investors about "machines overpowering humans", quantitative trading seems to have become the root of all evil behind A-share volatility.
However, if we set aside emotional biases and pierce through the fog of data, what is the real truth behind these doubts surrounding quantitative trading? Is it a cold-blooded "blood-sucking behemoth" or an overblown "scapegoat"?
01
Eye of the Storm
Recently, alongside the index pullback and sharp drops of some themed stocks, the narrative of "quantitative-driven sell-offs" has once again gained widespread traction.
In the eyes of some academic figures and market observers, the negative externalities of quantitative trading are becoming increasingly prominent. A highly representative view holds that the current market has degenerated into a zero-sum "casino", where quantitative institutions, leveraging their multiple advantages in capital, trading channels, and algorithms, are conducting "asymmetric harvesting". This perspective mainly focuses on three dimensions:
The first is speculation and sell-offs "detached from fundamentals". Critics argue that quantitative models do not focus on the true intrinsic value of enterprises, but instead amplify short-term market volatility through high-frequency trend tracking. When stock prices fall to touch preset thresholds, homogeneous sell-offs by trading machines create a negative feedback loop of "decline — stop-loss — further decline".
The second is the "privileged" nature of trading methods. In the view of traditional investors, tactics such as slow gradual declines after a false bullish push, precise order-blocking and order cancellations, are all evidence that quantitative institutions use technological advantages to conduct dimensionality-reduction strikes on ordinary traders. What makes ordinary investors feel even more unfair is the speed gap: although the detailed implementation rules issued by regulators have imposed certain restrictions on quantitative trading speed, the standard of no more than 300 transactions per second still constitutes a one-sided advantage over ordinary investors.
A director of investor relations at a listed company also complained on their social media feed that they do not oppose quantitative investment and recognize the advantages brought by technological progress, but technological progress should not negate the fundamental cornerstone of the capital market. They then targeted the factor settings of some quantitative strategies: "I have no problem with fundamental quantitative trading, but factors should not all be set to sentiment, momentum, and keyword-based parameters."
02
Confessions of Algorithms
Facing the overwhelming wave of criticism, the quantitative industry has not remained silent.
A tens-of-billion-scale private quantitative institution in Shanghai stated that the underlying logic of quantitative investment is built on massive diversification. Since the vast majority of quantitative stock trades are based on diversified positions across thousands of individual stocks, there are strict upper limits on the position size of a single stock (usually no more than 1%-3% of the net value for a single stock). The capital scale is insufficient to independently manipulate the trend of a single stock to create a high-volume breakout. To independently control a single stock to drive continuous rises and long-term gradual declines requires concentrated large-scale single-source capital, which is a characteristic of market manipulation, and naturally conflicts with the underlying rules of quantitative trading that feature diversified positions and strict risk control. The so-called "buying back at low positions" is simply the model judging that valuations have returned to normal after an excessive decline, rather than a "targeted harvesting" of retail investors' chips. Anthropomorphizing the market's normal mean reversion behavior into a "bet between market manipulators and retail investors" is a typical example of "attribution fallacy".
At the same time, some market voices claim that quantitative trading causes stock prices to decouple from corporate fundamentals. This tens-of-billion-scale private quantitative institution argues that attributing short-term stock price volatility to quantitative trading ignores core variables beyond fundamentals such as macro liquidity, risk appetite, and policy expectations. In 2015, when the scale of quantitative trading in the A-share market was very small, severe market volatility still occurred. The underlying factors of mainstream quantitative strategies (especially fundamental quantitative trading and statistical arbitrage) are highly dependent on financial data, valuation ratios, and industry prosperity. They do not price assets out of thin air, but use mathematical models to reflect newly released financial reports or macro data into prices faster and more rigorously. Rather than saying quantitative trading decouples stock prices from fundamentals, it compresses the time it takes for information to be reflected in prices — accelerating the speed of "price returning to value".
Another tens-of-billion-scale private quantitative fund defended itself from the perspective of "quantitative short selling", stating that in public perception, securities lending is almost equated with quantitative trading. But in reality, mainstream domestic quantitative products — whether index enhancement or quantitative long strategies — are essentially stock long strategies. Their core demand is to always maintain high-position operations, and obtain Alpha (excess) returns that outperform the index by continuously optimizing weights in the portfolio. This means quantitative funds are among the most steadfast "bulls" in the A-share market. When the broader market falls across the board, fully-positioned quantitative funds will also suffer huge Beta (average returns that follow market movements) losses. Even if some neutral strategies use stock index futures, it is to hedge systematic risks to isolate pure excess returns, rather than engaging in subjective directional "naked short selling".
In addition, regarding high-frequency trading that has long been criticized by investors, the interviewed private quantitative institutions stated that high-frequency trading, which corresponds to medium and low-frequency trading, is a false proposition in the A-share market. High-frequency trading refers to a trading method with extremely short position-holding cycles that aims to profit from bid-ask spreads. Such high-frequency trading mainly exists in the futures market under the T+0 trading system, where buying and selling can be completed within an extremely short time. However, because the stock market implements the T+1 trading system, high-frequency trading in the true sense cannot exist.
03
Fading Golden Body
Setting aside the clash of ideas, the private fund performance data for the first half of 2026 shows that even the "clockwork sickle" has had its edge blunted.
Data from Private Equity PaiPaiWang shows that as of June 30, 2026, the 1236 stock quantitative long products with publicly displayed performance achieved an average return of 16.25% in the first half of the year, roughly on par with the 17.32% return in the same period last year. However, the average excess return was only 3.11%, a significant drop from 14.17% in the same period last year. This means the returns of stock quantitative long products in the first half of the year mainly benefited from Beta returns brought by index rises, and the difficulty of obtaining Alpha returns has increased significantly.
In terms of specific strategies, performance differentiation is quite obvious. The CSI 500 Index and CSI 1000 Index enhancement strategies, which were regarded as "excess return ATMs" in the past few years, have entered a period of adjustment. According to data from Chaoyang Yongxu, in the first half of 2026, the excess return of private equity 500 enhancement products was -0.5%. Although a 0.3% excess return was achieved in the second quarter, there was still no obvious breakthrough overall. Private equity CSI 1000 enhancement was one of the varieties under the greatest pressure in the second quarter. Data shows that the excess return of private equity CSI 1000 enhancement products in the first half of 2026 was only 0.02%, and the single-quarter excess return in the second quarter was -1.2%, failing to continue the previous upward trend.
Li Chunyu, fund manager of FOF (Fund of Funds) at Rongzhi Investment under the PaiPaiWang Group, stated that in the first half of 2026, stock quantitative long products overall kept pace with the index gains, but excess returns narrowed significantly. The main reasons include: First, extreme market differentiation suppresses diversified positions. The A-share market shows a K-shaped trend, with 40% to 50% of trading volume concentrated in the top 5% popular technology stocks. Quantitative index enhancement models emphasize broad coverage and high diversification, and a large number of non-hot small and mid-cap stocks have stagnated or even fallen, directly dragging down portfolios and compressing the space for Alpha acquisition. Second, factor failure overlaps with strategy homogenization. While the momentum factor remains strong, reversal, mean reversion, and small-cap factors continue to move in the opposite direction. As the industry scale continues to expand, and most institutions share similar price-volume factors and frameworks, homogeneous crowding has diluted excess returns across massive amounts of capital. Third, style mismatch. Capital highly favors technology growth and momentum, while low-valuation and low-volatility factors are weak. Although dividend index enhancement has positive Alpha, the losses on the Beta side cannot be offset. Stock quantitative long strategies also struggle to outperform broad-based index enhancement strategies that focus heavily on technology leading stocks when there is no clear main line of rotation in the market.
04
Ecological Reshaping
In this protracted debate, how exactly should investors objectively and rationally view the real impact of quantitative trading on China's capital market?
An official from a private fund rating institution believes that first of all, we must recognize both the progressiveness and limitations of this tool. The role of quantitative trading in accelerating market price discovery and providing medium and short-term liquidity cannot be denied. He further stated that the crux is not to eliminate quantitative trading, but to achieve "rule equalization". What triggered public anger this time is not the trading method itself, but the sense of unfairness. When individual investors trade based on public information, while specific institutions can pay high fees to access premium market data and order submission channels, this gap in infrastructure and information access will be infinitely magnified in a weak market.
A senior market participant argues that simply attributing short-term stock price volatility to "malicious short selling" by a certain type of capital is a form of intellectual laziness. From macro liquidity, economic fundamental expectations, to high-level volatility in the global technology cycle, every rise and fall of the A-share market is the result of resonance across a complex system. At a time when technology stock valuations are already at historical highs, even without quantitative trading, the outflow of profit-taking positions and the collapse of market sentiment would still lead to a pullback.
However, the market's uproar and investors' anxiety do not have to end in fruitless emotional outbursts. The calls for "rule equalization" and demands for standardized quantitative trading have already been substantially delivered to the regulators' desks.
On July 20, Wu Qing, Chairman of the China Securities Regulatory Commission, conducted a research visit to a securities business office in Beijing and chaired an investor symposium. In this face-to-face exchange, 8 investor representatives covering large, medium, small, and retail investors spoke freely. Notably, the representatives not only put forward macro suggestions such as strengthening counter-cyclical regulation in the primary and secondary markets, taking multiple measures to guide medium and long-term capital into the market, further pushing listed companies to increase dividend payouts, and raising the cost of securities-related illegal crimes, but also directly addressed current market pain points — explicitly proposing to standardize the development of quantitative trading and AI (Artificial Intelligence) applications.
Wu Qing stated at the symposium, "The vast number of investors are the foundation of the market, and the most important participant group in the capital market."
"The CSRC will continue to promote risk prevention, strengthened regulation, and high-quality development of the capital market in a coordinated manner, make every effort to maintain stable market operation, focus on improving the transparency and authenticity of listed companies to better reward investors, urge industry institutions to operate in a standardized manner and improve investor service levels, continuously improve the long-term mechanism for investor protection, resolutely safeguard the open, fair, and just market order, and allow investors to better share the fruits of high-quality economic and capital market development," Wu Qing further added.
This article is from the WeChat Official Account "Economic Observer", written by Hong Xiaotang, and published with authorization from 36Kr.