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We propose a novel machine learning approach for probabilistic forecasting of hourly day-ahead electricity prices. In contrast with the recent advances in data-rich probabilistic forecasting, which approximates distributions with few…

General Economics · Economics 2025-07-04 Jozef Barunik , Lubos Hanus

We propose a new structural model that can compute the electricity spot and forward prices in two coupled markets with limited interconnection and multiple fuels. We choose a structural approach in order to represent some key…

Mathematical Finance · Quantitative Finance 2017-04-21 Clemence Alasseur , Olivier Feron

We consider a novel use case for the Double Heston model (Christoffersen et al,, 2009), where the two Heston sub-variances have different spot/volatility correlations but the same volatility of volatility and mean reversion speed. This…

Pricing of Securities · Quantitative Finance 2026-02-03 Mark Higgins

We consider stochastic volatility models under parameter uncertainty and investigate how model derived prices of European options are affected. We let the pricing parameters evolve dynamically in time within a specified region, and…

Mathematical Finance · Quantitative Finance 2018-07-12 Samuel N. Cohen , Martin Tegnér

We propose a multivariate elastic net regression forecast model for German quarter-hourly electricity spot markets. While the literature is diverse on day-ahead prediction approaches, both the intraday continuous and intraday call-auction…

Statistical Finance · Quantitative Finance 2018-11-22 Christopher Kath , Florian Ziel

In the classical model of stock prices which is assumed to be Geometric Brownian motion, the drift and the volatility of the prices are held constant. However, in reality, the volatility does vary. In quantitative finance, the Heston model…

Pricing of Securities · Quantitative Finance 2019-10-21 Arunangshu Biswas , Anindya Goswami , Ludger Overbeck

Most models for barrier pricing are designed to let a market maker tune the model-implied covariance between moves in the asset spot price and moves in the implied volatility skew. This is often implemented with a local…

Pricing of Securities · Quantitative Finance 2014-04-16 Mark Higgins

Accurate day-ahead electricity price forecasting is essential for residential welfare, yet current methods often fall short in forecast accuracy. We observe that commonly used time series models struggle to utilize the prior correlation…

Machine Learning · Computer Science 2024-08-20 Linian Wang , Jianghong Liu , Huibin Zhang , Leye Wang

Electricity price forecasting supports decision-making in energy markets and asset operation. Probabilistic forecasts are increasingly adopted to explicitly quantify uncertainty, typically issued as quantile predictions or ensembles of the…

Statistical Finance · Quantitative Finance 2026-04-22 Simon Hirsch , Florian Ziel

The participation of consumers and producers in demand response programs has increased in smart grids, which reduces investment and operation costs of power systems. Also, with the advent of renewable energy sources, the electricity market…

Machine Learning · Computer Science 2022-07-29 Nafise Rezaei , Roozbeh Rajabi , Abouzar Estebsari

How does dynamic price information flow among Northern European electricity spot prices and prices of major electricity generation fuel sources? We use time series models combined with new advances in causal inference to answer these…

Applications · Statistics 2011-10-26 Egil Ferkingstad , Anders Løland , Mathilde Wilhelmsen

We discuss stochastic modeling of volatility persistence and anti-correlations in electricity spot prices, and for this purpose we present two mean-reverting versions of the multifractal random walk (MRW). In the first model the…

Statistical Finance · Quantitative Finance 2015-06-04 Martin Rypdal , Ola Løvsletten

Mounting empirical evidence suggests that the observed extreme prices within a trading period can provide valuable information about the volatility of the process within that period. In this paper we define a class of stochastic volatility…

Statistical Finance · Quantitative Finance 2009-01-12 Abel Rodriguez , Henryk Gzyl , German Molina , Enrique ter Horst

In this paper analytic formulas for electricity derivatives are calculated. To this end, we assume that electricity spot prices follow a 3-regime Markov regime-switching model with independent spikes and drops and periodic transition…

Pricing of Securities · Quantitative Finance 2012-03-27 Joanna Janczura

We analyze the relative price change of assets starting from basic supply/demand considerations subject to arbitrary motivations. The resulting stochastic differential equation has coefficients that are functions of supply and demand. We…

Theoretical Economics · Economics 2020-08-26 Carey Caginalp , Gunduz Caginalp

Modeling price risks is crucial for economic decision making in energy markets. Besides the risk of a single price, the dependence structure of multiple prices is often relevant. We therefore propose a generic and easy-to-implement method…

Econometrics · Economics 2023-03-03 Oliver Grothe , Fabian Kächele , Fabian Krüger

The liberalization of electricity markets and the development of renewable energy sources has led to new challenges for decision makers. These challenges are accompanied by an increasing uncertainty about future electricity price movements.…

Applications · Statistics 2018-09-12 Florian Ziel , Rick Steinert

Building on a prominent agent-based model, we present a new structural stochastic volatility asset pricing model of fundamentalists vs. chartists where the prices are determined based on excess demand. Specifically, this allows for…

Economics · Quantitative Finance 2016-05-02 Radu T. Pruna , Maria Polukarov , Nicholas R. Jennings

Continuous intraday electricity markets play an increasingly important role in short-term trading and balancing, yet decision-making under rapidly evolving price dynamics remains challenging. This paper proposes a comprehensive framework…

Applications · Statistics 2026-05-14 Andrzej Puć , Joanna Janczura

We address the need for forecasting methodologies that handle large uncertainties in electricity prices for continuous intraday markets by incorporating parameter uncertainty and using a broad set of covariables. This study presents the…

Applications · Statistics 2025-09-11 Daniel Nickelsen , Gernot Müller