Calibration of One- and Two-Factor Models For Valuation of Energy Multi-Asset Derivative Contracts

TL;DR

This paper investigates the calibration of one- and two-factor models for energy derivatives, addressing data irregularities and joint modeling of multiple energy prices to improve valuation accuracy.

Contribution

It introduces methods for calibrating multi-factor energy models using real-world data with missing points and applies joint calibration to multiple regional energy prices.

Findings

Effective calibration techniques for irregular energy data

Successful joint calibration of multiple energy price models

Improved modeling of regional energy price dynamics

Abstract

We study historical calibration of one- and two-factor models that are known to describe relatively well the dynamics of energy underlyings such as spot and index natural gas or oil prices at different physical locations or regional power prices. We take into account uneven frequency of data due to weekends, holidays, and possible missing data. We study the case when several one- and two-factor models are used in the joint model with correlated model factors and present examples of joint calibration for daily natural gas prices at several locations in the US and for regional hourly power prices.