Speeding up the pricing of energy derivatives

Why energy markets are hard to model

Energy prices—for electricity, gas, or oil—are known for sudden spikes, sharp reversals, and other erratic behaviour that standard financial models struggle to capture. More sophisticated models exist, but they are often slow to run and tailored to specific type of market behaviour. This limits their use in real-world trading desks and risk management, where speed and flexibility are essential.

A single method that works across many models

We introduce a unified simulation framework that works for a broad family of market models, commonly used in energy finance: the Lévy-driven Ornstein-Uhlenbeck. Unlike existing techniques, which require a different algorithm for each model, the new approach allows the efficiently simulation any of these processes. This means practitioners can test and price derivatives under different market assumptions without changing their core simulation tool.

What makes it fast and practical

The method uses a combination of numerical techniques (Fast Fourier Transform and complex integration) that together cut computational time by at least ten times compared with current benchmarks. For example, what used to take minutes can now be done in seconds, while maintaining the same level of pricing accuracy. The framework also gives users clear control over the trade-off between speed and precision, making it suitable both for quick estimates and for high-stakes valuations.

Pricing the instruments traders actually use

The researchers test their method on two common types of energy derivatives: European and Asian options. These are widely traded instruments used by utilities, oil majors, and investment funds to hedge price risk or speculate on future movements. In all tests, the new method produced prices as accurate as existing slower algorithms, but at a fraction of the time.

What this means for the energy finance industry

Faster pricing engines allow risk managers to run more scenarios, traders to respond more quickly to market moves, and researchers to explore a wider range of possible market behaviours. By removing computational bottlenecks, the framework makes advanced market models more accessible for day-to-day use in the energy sector.

Key takeaways

• A new simulation method that works across many different market models, removing the need for model-specific algorithms.
• It is at least ten times faster than existing approaches, with no loss of accuracy.
• The method is tested on real-world energy derivatives, including European and Asian options.
• Faster simulations enable better risk analysis, more agile trading, and broader use of sophisticated models in practice.

Read the full paper

Fast and General Simulation of Lévy-driven Ornstein-Uhlenbeck processes for Energy Derivatives

Authors

Pietro Manzoni

Pietro is a research fellow at the University of Edinburgh Business School.

Roberto Baviera

Roberto is Professor in Financial Engineering at Politecnico di Milano, Italy.