The trading floor of InCommodities, on a commercial estate in the Danish city of Aarhus, shows off a dynamic, new side of Europe’s energy markets.
Youthful traders at the company, part-owned by Goldman Sachs, keep their eyes on banks of huge screens, watching for the perfect moment to buy or sell electricity. Other staff are developing algorithms that can help them to do the job far more efficiently than a mere human brain.
All are pursuing an edge in the increasingly complex renewable energy market that has developed as wind and solar generation have grown at the expense of fossil fuels. A mix of high potential profits, intellectual challenge and a role in the transition to a green economy have drawn dozens of smart young trading entrepreneurs to set up ventures both in Aarhus and Aalborg, just over 100km away. They compete with established players such as Equinor’s Danske Commodities in an area that Daniel Andersen, InCommodities’ chief executive for Europe, called the “Silicon Valley of energy trading”.
Andersen said after showing off the trading floor that the expansion of renewable energy generation would increase demand for the services of companies like his.
He added that the trading had a “stabilising effect” on the naturally volatile market, removing bottlenecks in the distribution of electricity.
“It’s incredibly challenging and incredibly fun,” Andersen said. “People get motivated by it.”
That volatility reflects the market’s reliance on changing natural conditions and fluctuating demand. It can move for reasons as small as the strength of the sun on a solar panel in Madrid, the angle of a wind turbine in the North Sea or extra orders at a factory in southern Germany.
The greater complexity and vast amounts of data have given sophisticated trading algorithms far greater importance, creating opportunities for traders such as InCommodities that can design and deploy them.
Andersen said increasing renewable generation would generate growing amounts of data.
“You need to be able to cope with this increase in data,” he said.
However, regulators are also starting to pay closer attention to the rise of automated trading. In a report last year, the Netherlands Authority for Consumers and Markets (ACM) said that while the trend brought benefits such as greater liquidity, it also came with risks. These included greater volatility, lower transparency and unintended market manipulation, it said.
Ian McGowan, head of compliance at InCommodities, accepted there was scope for greater understanding of how algorithms interact with one another.
“With greater quantities [of algorithms], the risk of inadvertent market conduct increases,” he said.
The new market’s emergence reflects how Europe’s energy generation has been transformed. Less than 10 per cent of the continent’s energy came from renewable sources 20 years ago, while the current figure is higher than 25 per cent. Spot prices for energy on the market in Germany — the continent’s biggest power consumer — can swing from negative on days when there is too much power to more than €600 per megawatt hour on days of “Dunkelflaute” when the sun is hidden and the wind is light.
Mads Schmidt Christensen, vice-president of strategy at Danske Commodities, said the task of forecasting, balancing and optimising renewable energy production required “extreme dedication”. Traders needed to monitor short-term factors such as levels of cloud cover, small changes in wind patterns and the effect of ice on wind turbines, he added.
“As the share of renewables in the energy mix continues to increase, the need for real-time balancing of energy markets will only grow bigger,” he said.
Traders also increasingly need to be able to shift their positions at the last minute to account for any surprises in an increasingly complex market.
That has accelerated the adoption of automated trading, according to the study last year by the Netherlands’ ACM.
“The energy transition is a development that drives the use of algorithms even further,” the study said. “The generation of renewable energy is less predictable, as a result of which the need for traders to manage their positions at the last minute increases.”
InCommodities entered the market in 2017, with what Andersen described as a “core belief” that technology and algorithms were “the way forward”.
Energy markets had been shaped by factors including geopolitical tensions, news, policymaking and regulation, advances in technology, demand flexibility, macroeconomic conditions and physical conditions, he pointed out.
“Algorithms are a way to navigate all that data, extract the relevant information and understand how it’s going to impact prices,” Andersen said.
The market has been particularly shaped, meanwhile, by the high profits that traders were able to generate when energy prices rose sharply in 2022 after Russia’s full-scale invasion of Ukraine. InCommodities generated €1.06bn in post-tax profits for 2022, up from €112mn the year before, while Danske Commodities generated €1.47bn on the same measure, up from €303mn in 2021.
While profits have since returned to closer to normal levels, 2022’s bumper returns encouraged the establishment of a series of new competitors. Aros Commodities, Pure Power Trading, Aarhus Energy and Asgard — mostly owned by ambitious young founders — were all established in Aarhus and Aalborg in 2023.
Marc Zimmerlin, a partner at the consultancy Oliver Wyman, said the power trading market had changed as smaller participants built the financial strength to attract staff. Hedge funds and banks were also returning to the market after previously scaling back, he added.
There is growing interest across the range of companies in automated trading. According to Epex, a European power exchange, 70 per cent of volumes traded on the market in 2024 were traded via automated systems, compared with only 44 per cent as recently as 2020.
While some traders rely on “off the shelf” systems bought from others, some market participants have invested heavily in developing proprietary software to give themselves an extra competitive edge.
Adam Perkins, a partner in Oliver Wyman’s energy and natural resources practice, said it was clear from their profit figures that some participants had better models.
The ACM report predicted that automated trading’s share of volumes would continue to increase, as manual trading became less competitive. Algorithms are also growing more sophisticated and, in some cases, can now learn as they go. Such algorithms could improve markets’ liquidity and make price formation more efficient, the study predicted.
However, it also said that the use of algorithms could sometimes inadvertently manipulate the market.
It warned that, when two algorithms engaged in “robot battles” in a market, they could trade so fast that it sent the market “false or misleading signals”.
Acer, a body that co-ordinates the work of Europe’s energy regulators, also expressed concern. It said the rapid speed of algorithmic trading, with orders placed in milliseconds, posed “challenges for surveillance teams at venues and regulators alike”, although it stressed that adequate monitoring systems were in place.
At the office in Aarhus, InCommodities’ McGowan recognised there were some legitimate concerns about the effects of greater algorithmic trading. There could be unexpected outcomes as volumes increased, he said.
“The pace of change over the past few years has been significant,” he said.
New market rules had been introduced to tackle some of the issues, he added, although guidance for companies such as his on what they meant was “virtually non-existent”.
He insisted, however, that his company wanted to get its approach right as it grew.
“We want to pioneer best practices,” he said. “We recognise our responsibilities in the markets.”