There is an urgent need to patch the loopholes in quantitative trading in the stock market

Mondo Finance Updated on 2024-02-24

On February 20, the Shenzhen Stock Exchange and the Shanghai Stock Exchange respectively took measures to restrict trading on the relevant ** accounts under the name of Ningbo Lingjun Investment, and initiated the procedure of public reprimand and disciplinary action. The reason is that Ningbo Lingjun Investment sold frantically within one minute of opening 256.7 billion yuan, which led to a rapid decline in the index, once triggered panic in A-shares.

As soon as the punishment was disclosed, it immediately sparked heated discussions on the whole network, and netizens were shocked and surprised, because they had investigated and dealt with continuous longs before, and this was the first time in several years that they were investigated and dealt with shorts. Of course, the regulatory authorities launched the penalty procedure this time, releasing a strong regulatory signal: we will not tolerate and tolerate violations of institutional quantitative trading that affect the smooth operation of the market and damage the legitimate rights and interests of investors.

The essence of quantitative trading is a method of using computers and mathematical models to conduct first-class transactions, through the calculation and analysis of a large number of data in the market, looking for rules and trends, and on this basis to formulate trading strategies and transactions, the purpose of which is to make up for the limitations of professional knowledge, personal experience, subjective judgment, trading sentiment and other aspects of manual operation, and continuously improve the speed and accuracy of decision-making, and effectively control the risk of trading; The biggest advantage is that it can find some opportunities that are difficult to find artificially, and carry out risk-free or low-risk arbitrage operations, which greatly improves trading efficiency. At present, many large financial institutions and hedges** have actively adopted quantitative trading to make investment and trading decisions to improve ROI.

Although quantitative trading has far advantages over manual operations, it is not an invincible "bible", and its inaccurate data analysis can lead to strategy failure, it takes a lot of time to study quantitative trading algorithms, and there is a risk that the simulated results are inconsistent with the actual trading results. In particular, some large investment institutions may use their trading advantages to implement high-frequency trading, long or short, which will have a greater impact on the market.

At present, in some developed economies, about 70% of the transactions are decided by computers, and in China, this figure is close to 50%; As of the end of 2021, more than 400 institutions in China have engaged in such transactions, and it will increase significantly in the future, and the proportion of quantitative transactions will be higher and higher.

From the Ningbo Lingjun investment incident, there are still many problems in quantitative trading: first, the investment institutions operate arbitrarily, lack of strict reporting system, and the access arrangement of "report first, then trade" is not in place, which can easily lead to blind speculation by institutions; Second, the authorization management of quantitative trading is weakened, the differentiated charging mechanism is not perfect, and there is a lack of strong binding force on quantitative trading; Third, the monitoring and monitoring standards for abnormal transactions are not perfect, and the supervision of abnormal transactions and abnormal order cancellations is not in place, which is prone to high-frequency and huge transactions; Fourth, the monitoring and regulation of leveraged quantitative products are not clear and imperfect, which is easy to breed risks.

Obviously, the quantitative trading mechanism is two sides of the same coin, and the flaws or loopholes of this trading mechanism need to be patched in order to maximize the strengths and avoid the weaknesses.

On the one hand, we should learn from the experience of foreign quantitative trading supervision, improve and consolidate the quantitative trading mechanism, and prevent high-frequency trading from causing negative impacts on the market. First of all, the first quantitative programmatic transaction report and management system issued by the previous exchange should be supplemented and improved in a timely manner, a special reporting system for quantitative trading and corresponding regulatory arrangements should be established, the "report before trading" procedure should be strictly implemented, and the trading behavior of "cutting first and then playing" should be strictly prohibited. At the same time, we continue to use technological innovation to supervise quantitative trading and grasp the trading dynamics in a timely manner; In addition, we will establish and improve the long-term assessment mechanism to curb the short-term investment behavior of institutional investors, avoid market fluctuations and adjustments, continuously promote the scientific quantitative trading mechanism, eliminate the homogeneous competition of investment institutions, avoid the occurrence of strategic convergence and transaction resonance, and promote the improvement of the core competitiveness of all investment institutions. At the same time, through the improvement of the quantitative trading mechanism, we will continuously improve the compliance awareness and risk awareness of investment institutions, and improve the ability of trading institutions to resist risks. On February 20, the Shanghai Stock Exchange and the Shenzhen Stock Exchange respectively issued reports on the "Stable Implementation of the Quantitative Transaction Reporting System of the Shanghai Stock Exchange" and the "Stable Implementation of the Quantitative Trading Reporting System of the Shenzhen Stock Exchange", pointing out that the continuous strengthening of the monitoring and analysis of quantitative trading, especially high-frequency trading, and the dynamic evaluation and improvement of the reporting system undoubtedly played a role in patching the quantitative trading system in a timely manner.

In addition, regulators should increase guidance to quantitative trading institutions, cultivate compliance awareness of investment institutions, and improve self-discipline capabilities. The main purpose is to urge quantitative trading institutions to improve their trading models, strictly control the transaction progress, transaction constraints, and control the transaction rhythm, so as to ensure smooth and balanced transactions in the whole process of trading, effectively maintain the normal market trading order, and fully protect the legitimate rights and interests of investors.

On the other hand, we will strengthen supervision and create a financial environment that strictly supervises quantitative trading. First of all, starting from the technical point of view, the stock exchanges should increase the investment in quantitative trading monitoring technology, make full use of big data information technology, conduct comprehensive monitoring of all kinds of quantitative trading institutions, improve the ability to detect high-frequency trading caused by abnormal movements, and admonish and stop the signs of timely discovery, eliminate the problem in the bud, completely eliminate the regulatory vacuum, and make the sword of strict supervision always hang above the head of quantitative trading institutions. Second, increase penalties, enhance regulatory deterrence, and form a strict regulatory atmosphere. Thirdly, build a social supervision system, give full play to the role of the China Securities Regulatory Commission, the stock exchange, the self-regulatory organization of the ** industry association, listed companies, shareholders and other joint supervision, set up a regulatory information exchange platform, and form an all-round and effective supervision of quantitative trading behavior.

Written by Mo Kaiwei.

Edited by Yue Caizhou.

Proofread by Zhao Lin.

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