The Forecasting Tools Traders Trust: Lessons from a European Energy Market Survey

Until recently, European power prices were predictable. That’s because electricity demand was relatively flat, and power generation came primarily from large coal, nuclear, and natural gas plants.  

Today, volatility has replaced power price predictability and introduced challenges and opportunities for traders seeking to navigate European power markets. The volatility comes from a combination of factors, including extreme weather, geopolitical events, and dramatic changes in demand and Europe’s generation mix.  

For example, renewables accounted for slightly less than half of EU electricity generation in 2024, with solar surpassing coal for the first time. As more gigawatts of wind and solar flood the grid, and electric vehicles, heat pumps, and data centers drive up demand, power prices will be anything but predictable.   

Energy Exemplar and Utility Dive’s studioID surveyed 70 power market professionals across the EU and UK to explore how they view pricing volatility and the tools they use to navigate it. 

The key takeaway? While traders are deploying various price forecasting tools — including statistical models, artificial intelligence (AI) and machine learning (ML), and market data — the true power lies in fundamental models, which deliver the accuracy today’s market chaos demands. 

Download Now: What European Traders Say About Forecasting in Today's Volatile Markets [Free Report]

Statistical models were built for the past

The power traders surveyed were clear-eyed about the importance of accurate pricing forecasts. Nearly half (47%) rated financial losses as the top consequence of inaccurate forecasts. That financial pain can come in many flavors, including ineffective hedges, regulatory penalties, and bad trades. 

Despite these steep risks, just 47% of traders surveyed rated the ML/AI and statistical models they use to forecast prices and guide trades as “very” accurate. And only 11% rated those models as “extremely” accurate. 

European power traders are wary about the accuracy of their models for good reason. By design, statistical models use historical trends to forecast future outcomes. That works just fine when markets are stable. 

However, the influx of renewable generation, growing electricity demand, and atypical weather conditions mean the past is a poor predictor of the future. For example, last year “Dunkelflaute” conditions — when low wind and little sunlight slash wind and solar generation — caused prices to spike over €1,000 per megawatt hour. A few months later, a glut of renewable power and low demand drove prices below zero. 

Statistical models built using historical data are not prepared to forecast a steady succession of unprecedented market conditions and prices. This is not news to European power traders: Over half (53%) of those surveyed said statistical models fail when unexpected events strike. With unexpected events now the norm in European power markets, statistical models will not suffice.  

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What are European Traders Using for Accurate Price Forecasts?

Discover the differences between Fundamental and Statistical models, and which models European Traders say are delivering more accurate price forecasts to help them reduce risk and financial losses. 

Fundamental models are designed for today's volatile market

Statistical models examine the past to provide insights about the future. Fundamental models embrace a very different approach. Instead of analyzing past trends, fundamental models develop price forecasts based on: 

• Real-time demand and supply
  
• Fuel and carbon prices
• Weather and renewable output
• Plant ramp rates and outages
• Grid congestion and flow-based coupling

Fundamental models produce price forecasts reflecting current and future market dynamics, even if those conditions have never been present. Traders using fundamental models saw dramatically higher accuracy in their price forecasts. In fact, 73% said these models were “very” or “extremely” valuable.  

The cost and complexity barrier

Traders know the value fundamental models bring. Given that, why aren’t more traders using them? Traders surveyed reported that both the perceived cost and time to build and maintain a fundamental model were major barriers to their use. Many also said they weren’t convinced that the improved accuracy provided by fundamental models was worth the effort. 

But there’s a flaw in that thinking. Nearly half (47%) of traders said inaccurate forecasts resulted in financial losses. Not investing in improved price forecast accuracy is already costing traders.  

Traders don’t have to build and maintain their own fundamental models. With Energy Exemplar’s PLEXOS® for Traders solutions, organizations can adopt pre-built or customizable fundamental models. Traders can use PLEXOS® Insights for Traders for out-of-the-box insights or PLEXOS® Playbook for Traders to customize and test their own assumptions in a pre-built fundamental model. 

Little about the future of electricity prices in Europe is predictable. Growing complexity will propel more volatility and uncertainty. Traders must move away from tools built for the past and move toward fundamental models that reflect market realities today and can anticipate where prices are headed next.  

Download the report for more insights into how traders are navigating today’s pricing volatility.  

Download the Exclusive Report

What European Traders Say About Forecasting in Today's Volatile Market

Download the report to gain exclusive insights into how traders are navigating today's pricing volatility.