Gaussian Volterra processes as models of electricity markets
Yuliya Mishura, Stefania Ottaviano, Tiziano Vargiolu

TL;DR
This paper introduces a non-Markovian Gaussian Volterra process-based model for electricity markets, analyzing arbitrage, market completeness, and providing explicit solutions for portfolio optimization and option pricing.
Contribution
It develops a novel framework using Gaussian Volterra processes for modeling electricity prices, characterizes market completeness, and derives explicit formulas for hedging and utility maximization.
Findings
Market models with Gaussian Volterra processes ensure no arbitrage under certain conditions.
Market completeness depends on the number of forward contracts and process kernels.
Explicit formulas for option prices and hedging strategies are derived.
Abstract
We introduce a non-Markovian model for electricity markets where the spot price of electricity is driven by several Gaussian Volterra processes, which can be e.g., fractional Brownian motions (fBms), Riemann-Liouville processes or Gaussian-Volterra driven Ornstein-Uhlenbeck processes. Since in energy markets the spot price is not a tradeable asset, due to the limited storage possibilities, forward contracts are considered as traded products. We ensure necessary and sufficient conditions for the absence of arbitrage that, in this kind of market, reflects the fact that the prices of the forward contracts are (Gaussian) martingales under a risk-neutral measure. Moreover, we characterize the market completeness in terms of the number of forward contracts simultaneously considered and of the kernels of the Gaussian-Volterra processes. We also provide a novel representation of…
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Taxonomy
TopicsElectric Power System Optimization · Capital Investment and Risk Analysis · Process Optimization and Integration
