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By Kasper Walet, Founder and Partner AI Energizer and Maycroft
I recently read a very interesting article in the Financial Times about how commodity trading firms are still lagging behind other trading sectors in using Artificial Intelligence solutions. but that the industry is trying hard to catch up. These findings are in line with my practical experiences in our advisory services business: AI Energizer.
Particularly in today’s market situation where margins are squeezed, commodity traders are looking for tools that could help them to increase profitability. Intelligent technologies such as robotic process automation and machine learning, offer new opportunities to improve process performance and realize significant cost savings. These technologies can be implemented in short sprints, focused on a specific problem, with manageable costs.
If you click here, you can read our white paper about successful AI projects we executed for two of the leading energy commodity trading firms in Europe.
Compared to other financial and industrial sectors, commodity traders are coming from way behind. Currency, equities and interest-rates investors have already used algorithms, machine learning and artificial intelligence to turn data into successful trades for years. Now, commodity traders are seeking ways of exploiting their information to help them profit from price swings as well. It really is a combination of knowing what to look for and using the right mathematical tools for it.
Traders are looking to gather data on a large scale and run machine-learning algorithms to find patterns linking fundamentals with price movements, thus improve decision-making in trading and, as a result, the profitability. With a properly trained algorithm and a sufficiently sized historical data set, a company using machine learning to identify patterns in the trading data - even when the data has inconsistencies – will reduce redundant trades and streamline the entire process. To accommodate all this commodity trading firms are investing in people, processes and systems to centralize their data.
Despite this new enthusiasm, the road to electronification may not come easily. One issue is that some of the larger commodities traders face internal resistance in centralizing information on one platform. With each desk in a trading house in charge of its profit-and-loss account, data are closely guarded even from colleagues. The move to ‘share all our data with each other’ is a very, very big cultural shift.
Another problem is that in some trading houses, staff operate on multiple technology platforms, with different units using separate systems. Rather than focusing on analytics, some data scientists and engineers are having to focus on harmonizing the platforms before bringing on the data from different parts of the company. Even where the digital infrastructure is in place, it may take some time before AI becomes a large part of commodities trading.
Company leaders should start with the following three steps:
Step 1: Focus on value
As AI can solve targeted problems, it's up to company leaders to identify applications that offer the most potential value. Demonstrating strong returns in a short time will convert the cynics. AI projects typically happen in a series of sprints and can be completed in around 3-4 months.
Step 2: Change Management
Automation alone does not save money or improve performance: People and processes will also have to change. This is an area where there is understandable anxiety; automation stokes fears that machines will take people's jobs. But practice suggests that many of the tasks being automated are activities people tend not to want to undertake, such as spending half the day pulling and loading data. Or they are tasks for which small automation can actually improve people's performance - for instance, by introducing predictive algorithms that help them make better decisions and free up their time for more rewarding, interesting, and higher value-add activities.
This is an entirely new way of working, and company leaders will need to ensure that both they and their people have the right knowledge and skills, such as programming and data science knowledge and process improvement skills - to be successful. And they'll need to ensure that everyone's mind-set and behaviors also shift accordingly.
Step 3: Strategy is King
The backbone of this new way of working is strategy. Companies need to know their own strengths. There will be "keep the lights on" activities that can become touchless, as well as differentiating activities that should become increasingly intelligent. Moreover, companies need to take a fresh look at their organizational structure to ensure that it gives teams the freedom to develop creative solutions and experiment.
Conclusion
Concluding we can say that digitization is increasingly driving trading, and needs to be embraced, as many commodities executives believe. “It’s another tool that traders have to understand.”
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Recent headlines on the oil industry have focused squarely on the upstream side: the amount of crude oil that is being produced and the resulting effect on oil prices, against a backdrop of the Covid-19 pandemic. But that is just one part of the supply chain. To be sold as final products, crude oil needs to be refined into its constituent fuels, each of which is facing its own crisis because of the overall demand destruction caused by the virus. And once the dust settles, the global refining industry will look very different.
Because even before the pandemic broke out, there was a surplus of refining capacity worldwide. According to the BP Statistical Review of World Energy 2019, global oil demand was some 99.85 mmb/d. However, this consumption figure includes substitute fuels – ethanol blended into US gasoline and biodiesel in Europe and parts of Asia – as well as chemical additives added on to fuels. While by no means an exact science, extrapolating oil demand to exclude this results in a global oil demand figure of some 95.44 mmb/d. In comparison, global refining capacity was just over 100 mmb/d. This overcapacity is intentional; since most refineries do not run at 100% utilisation all the time and many will shut down for scheduled maintenance periodically, global refining utilisation rates stand at about 85%.
Based on this, even accounting for differences in definitions and calculations, global oil demand and global oil refining supply is relatively evenly matched. However, demand is a fluid beast, while refineries are static. With the Covid-19 pandemic entering into its sixth month, the impact on fuels demand has been dramatic. Estimates suggest that global oil demand fell by as much as 20 mmb/d at its peak. In the early days of the crisis, refiners responded by slashing the production of jet fuel towards gasoline and diesel, as international air travel was one of the first victims of the virus. As national and sub-national lockdowns were introduced, demand destruction extended to transport fuels (gasoline, diesel, fuel oil), petrochemicals (naphtha, LPG) and power generation (gasoil, fuel oil). Just as shutting down an oil rig can take weeks to complete, shutting down an entire oil refinery can take a similar timeframe – while still producing fuels that there is no demand for.
Refineries responded by slashing utilisation rates, and prioritising certain fuel types. In China, state oil refiners moved from running their sites at 90% to 40-50% at the peak of the Chinese outbreak; similar moves were made by key refiners in South Korea and Japan. With the lockdowns easing across most of Asia, refining runs have now increased, stimulating demand for crude oil. In Europe, where the virus hit hard and fast, refinery utilisation rates dropped as low as 10% in some cases, with some countries (Portugal, Italy) halting refining activities altogether. In the USA, now the hardest-hit country in the world, several refineries have been shuttered, with no timeline on if and when production will resume. But with lockdowns easing, and the summer driving season up ahead, refinery production is gradually increasing.
But even if the end of the Covid-19 crisis is near, it still doesn’t change the fundamental issue facing the refining industry – there is still too much capacity. The supply/demand balance shows that most regions are quite even in terms of consumption and refining capacity, with the exception of overcapacity in Europe and the former Soviet Union bloc. The regional balances do hide some interesting stories; Chinese refining capacity exceeds its consumption by over 2 mmb/d, and with the addition of 3 new mega-refineries in 2019, that gap increases even further. The only reason why the balance in Asia looks relatively even is because of oil demand ‘sinks’ such as Indonesia, Vietnam and Pakistan. Even in the US, the wealth of refining capacity on the Gulf Coast makes smaller refineries on the East and West coasts increasingly redundant.
Given this, the aftermath of the Covid-19 crisis will be the inevitable hastening of the current trend in the refining industry, the closure of small, simpler refineries in favour of large, complex and more modern refineries. On the chopping block will be many of the sub-50 kb/d refineries in Europe; because why run a loss-making refinery when the product can be imported for cheaper, even accounting for shipping costs from the Middle East or Asia? Smaller US refineries are at risk as well, along with legacy sites in the Middle East and Russia. Based on current trends, Europe alone could lose some 2 mmb/d of refining capacity by 2025. Rising oil prices and improvements in refining margins could ensure the continued survival of some vulnerable refineries, but that will only be a temporary measure. The trend is clear; out with the small, in with the big. Covid-19 will only amplify that. It may be a painful process, but in the grand scheme of things, it is also a necessary one.
Infographic: Global oil consumption and refining capacity (BP Statistical Review of World Energy 2019)
| Region | Consumption (mmb/d)* | Refining Capacity (mmb/d) |
| North America | 22.71 | 22.33 |
| Latin America | 6.5 | 5.98 |
| Europe | 14.27 | 15.68 |
| CIS | 4.0 | 8.16 |
| Middle East | 9.0 | 9.7 |
| Africa | 3.96 | 3.4 |
| Asia-Pacific | 35 | 34.75 |
| Total | 95.44 | 100.05 |
*Extrapolated to exclude additives and substitute fuels (ethanol, biodiesel)
Market Outlook:
End of Article
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Source: U.S. Energy Information Administration, based on Bloomberg L.P. data
Note: All prices except West Texas Intermediate (Cushing) are spot prices.
The New York Mercantile Exchange (NYMEX) front-month futures contract for West Texas Intermediate (WTI), the most heavily used crude oil price benchmark in North America, saw its largest and swiftest decline ever on April 20, 2020, dropping as low as -$40.32 per barrel (b) during intraday trading before closing at -$37.63/b. Prices have since recovered, and even though the market event proved short-lived, the incident is useful for highlighting the interconnectedness of the wider North American crude oil market.
Changes in the NYMEX WTI price can affect other price markers across North America because of physical market linkages such as pipelines—as with the WTI Midland price—or because a specific price is based on a formula—as with the Maya crude oil price. This interconnectedness led other North American crude oil spot price markers to also fall below zero on April 20, including WTI Midland, Mars, West Texas Sour (WTS), and Bakken Clearbrook. However, the usefulness of the NYMEX WTI to crude oil market participants as a reference price is limited by several factors.
Source: U.S. Energy Information Administration
First, NYMEX WTI is geographically specific because it is physically redeemed (or settled) at storage facilities located in Cushing, Oklahoma, and so it is influenced by events that may not reflect the wider market. The April 20 WTI price decline was driven in part by a local deficit of uncommitted crude oil storage capacity in Cushing. Similarly, while the price of the Bakken Guernsey marker declined to -$38.63/b, the price of Louisiana Light Sweet—a chemically comparable crude oil—decreased to $13.37/b.
Second, NYMEX WTI is chemically specific, meaning to be graded as WTI by NYMEX, a crude oil must fall within the acceptable ranges of 12 different physical characteristics such as density, sulfur content, acidity, and purity. NYMEX WTI can therefore be unsuitable as a price for crude oils with characteristics outside these specific ranges.
Finally, NYMEX WTI is time specific. As a futures contract, the price of a NYMEX WTI contract is the price to deliver 1,000 barrels of crude oil within a specific month in the future (typically at least 10 days). The last day of trading for the May 2020 contract, for instance, was April 21, with physical delivery occurring between May 1 and May 31. Some market participants, however, may prefer more immediate delivery than a NYMEX WTI futures contract provides. Consequently, these market participants will instead turn to shorter-term spot price alternatives.
Taken together, these attributes help to explain the variety of prices used in the North American crude oil market. These markers price most of the crude oils commonly used by U.S. buyers and cover a wide geographic area.
Principal contributor: Jesse Barnett
Key findings