Heath-Jarrow-Morton meet lifted Heston in energy markets for joint historical and implied calibration

TL;DR

This paper introduces a novel calibration framework combining a Heath-Jarrow-Morton model with a lifted Heston stochastic volatility model to jointly fit historical and implied energy market data efficiently.

Contribution

It develops a sequential calibration procedure that decouples complex calibration steps, improving fit accuracy and computational efficiency in energy markets.

Findings

Achieves remarkable joint calibration fits on German power market data.

Enables realistic interpolation within the implied volatility hypercube.

Decouples calibration steps for simpler, more stable optimization.

Abstract

In energy markets, joint historical and implied calibration is of paramount importance for practitioners, yet notoriously challenging due to the need to align historical correlations of futures contracts with implied volatility smiles from the option market. We address this crucial problem with a multiplicative multi-factor Heath-Jarrow-Morton (HJM) model for forward curves, combined with a stochastic volatility factor coming from the lifted Heston model. We develop a sequential fast calibration procedure leveraging the Kemna-Vorst approximation of futures contracts: (i) historical correlations and the Variance Swap (VS) volatility term structure are captured through Level, Slope, and Curvature factors, (ii) the VS volatility term structure can then be corrected for a perfect match via a fixed-point algorithm, (iii) implied volatility smiles are calibrated using Fourier-based techniques. The main advantage of the proposed calibration framework is the decoupling of the calibration steps: each step tackles a simpler calibration subproblem and guaranties that the previously optimized parameters remain unchanged. Our model displays remarkable joint historical and implied calibration fits on the German power market and enables realistic interpolation within the implied volatility hypercube.