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Financial Associated Press, April 22 (Editor Zhao Hao) in order to gain a technological advantage over competitorsFinaltablepokerclubSome of the world's largest commodity traders are investing heavily in data processing and analysis.

In the current international oil trading systemFinaltablepokerclubIn addition to the two main forces of national oil companies and international oil companies, professional trading companies such as Victor and Trafigura are also extremely important market participants. Nowadays, they are also paying more and more attention to how to apply artificial intelligence to this physical industry.

"to some extent, this is an arms race," Russell Hardy, chief executive of Vitol, the world's largest oil trader, said at a summit earlier this month. He adds that artificial intelligence is mainly used in two scenarios: improving business efficiency and developing transaction advantages.

Hardy explained that the trading advantage requires the company to have stronger analytical skills than its competitors. "We are all trying to get to the moon earlier." Artificial intelligence is also more helpful to business efficiency than predicting the market in the short term, he adds.

It is understood that Victor is an unlisted company with about 1800 employees, with a record net profit of US $15.1 billion in 2022 and a net profit of about US $13 billion in 2023, making it one of the companies with the highest profit-employee ratio in the world.

"Best hedge fund"

Financial institutions such as hedge funds have increased competitive pressure in the sector in recent years, according to media analysts. Although they do not transport much physical goods, they have established lucrative financial businesses such as commodity-linked securities and other businesses.

Among them, hedge fund firm Citadel hired Sebastian Barrack from Macquarie as head of commodities trading in 2017 to expand into energy and raw materials. At the time, Barrack hired a weather forecasting team of 20 people, and now the trading team has expanded to more than 300 people.

In recent years, Castle Investment has overwhelmed Qiaoshui and other peers to become the "new king of global hedge funds". "We have access to a lot of data to give our investors a better understanding of the situation, especially in the areas of supply levels, demand patterns and logistics variables of oil and refined products," Barrack told the media.

He added that for data-led trading strategies, the trend of energy transformation will bring greater benefits because this new area of lack of historical information will increase complexity. More complex tools are needed to simulate the market. "the more complex the market, the more detailed the data, the better for us."

The field of power transaction

In addition, the ability to process large amounts of data is becoming more and more important in the fast-growing field of power transactions. McKinsey, the consultancy, estimates that data-driven trading firms earned 1/4 of global gas and electricity trading profits in 2022, up from 5 per cent in 2021.

That interest has also forced Trafigura, another commodities trading giant, to invest to keep up with the market, which set up its electricity trading division three years ago and made a record profit of $7.4 billion last year.

Richard Holtum, head of Trafigura's natural gas, electricity and renewable energy departments, said his team uploads large amounts of data to the cloud every day, "where artificial intelligence allows us to access this data in a better and more efficient way and improve our trading decisions. But what we know about AI may be just the tip of the iceberg. "

Last week, it was reported that the Bridge Water Fund had used artificial intelligence technology in its investments, mainly to manage some aspects of the fund and client portfolio, according to the information in part of ADV form 2A updated by the Securities and Exchange Commission at the end of March.

Qiaoshui Fund said in its information disclosure materials that with the development of computing technology, data analysis and related fields, portfolio management, trading, portfolio risk management and other investment processes are increasingly inclined to use tools such as generative artificial intelligence, large language models, machine learning, artificial neural networks and so on.