Overview
This use case builds an end-to-end electricity-pricing workflow from daily spot prices and monthly futures. The spot series is first analysed for seasonality, volatility, spikes and drawdowns, then decomposed into a deterministic seasonal component and a stochastic mean-reverting process. The stochastic component is modelled as an Ornstein-Uhlenbeck-style process with jumps, calibrated by maximum likelihood, and then simulated under both the real-world measure P and the risk-neutral measure Q. The framework ultimately links spot behaviour to futures calibration, risk premium estimation and derivative pricing.
Electricity is a particularly demanding market because prices display strong seasonality, rapid mean reversion, heavy tails and abrupt spikes. A simple Gaussian or random-walk model would miss the core economic behaviour. The case therefore combines seasonal regression, jump-aware mean reversion, Monte Carlo simulation and Longstaff-Schwartz valuation to create a practical pricing stack for power derivatives.
Business relevance
- Model spot-price seasonality and extreme price behaviour in a framework designed for electricity markets.
- Calibrate a risk-neutral price process to the observed futures curve and estimate the implied risk premium.
- Generate Monte Carlo price paths for valuation, stress testing and exposure analysis.
- Price flexible power derivatives such as Bermudan calls while quantifying exercise behaviour and uncertainty.
- Support energy trading, hedging, procurement and risk management with one coherent model pipeline.
Solution
The solution models electricity prices as a seasonal component plus a strongly mean-reverting stochastic process with occasional jumps. This captures recurring calendar effects, short-lived spikes and rapid reversion without treating power prices like a standard Gaussian asset.
The physical process can then be transformed into a risk-neutral process by calibrating to the observed futures curve and estimating the implied market price of risk. Monte Carlo simulation and Longstaff-Schwartz can subsequently support scenario generation, hedging and valuation of flexible electricity derivatives such as Bermudan options.