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Risks
Special Issues
Financial Derivatives and Hedging in Energy Markets
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Financial Derivatives and Hedging in Energy Markets

A special issue of Risks (ISSN 2227-9091).

Deadline for manuscript submissions: closed (31 March 2025) | Viewed by 1920

Special Issue Editors

Dr. Viviana Fanelli

E-Mail Website
Guest Editor
Department of Economics, University of Foggia, 71121 Foggia, Italy
Interests: stochastic models; asset pricing; arbitrage strategies; dynamic models; commodity finance and markets; interest rate and credit risk modelling.
Dr. Michele Bufalo

E-Mail Website
Guest Editor
Department of Economics and Finance, University of Bari, 70121 Bari, Italy
Interests: stochastic processes; stochastic models for interest rates; Skew-Geometric Brownian motions and applications in finance; forecasting: interest rates forecasting; natural catastrophes (NatCat) forecasting; option pricing in incomplete markets; generalized Trotter-Kato formulas for option pricing problems in incomplete markets; option pricing under changes of numeraire; Expected transaction costs; and generalized Barone-Adesi Whaley formula for turbolent markets

Special Issue Information

Dear Colleagues,

The liberalization of energy markets has given rise to new patterns of financial product prices and the need for models that could accurately describe price dynamics as they grew exponentially to improve decision-making for all the agents involved in energy issues.

Energy derivatives play an important role in the modern financial system and are widely used for speculation, industrial production planning, and risk hedging. In the global energy markets, energy derivatives enable participants to manage the risk associated with volatile prices, speculate on future price movements, and achieve investment diversification. Definitively, they encourage better price discovery and risk transfer.

Therefore, mathematical and statistical tools are important for estimating, implementing and calibrating quantitative models, pricing and trading energy-linked products, and managing basic and complex portfolio risks.

Topics for consideration in this Special Issue include, among others, the following:

  • The pricing of energy derivatives;
  • Hedging with futures, options, and swaps;
  • Portfolio risk management;
  • Modeling dynamic hedge ratios;
  • Mathematical finance;
  • Advanced hedging measures;
  • Risk-neutral valuation;
  • The arbitrage theory;
  • Derivative trading.

Dr. Viviana Fanelli
Dr. Michele Bufalo
Guest Editors

Manuscript Submission Information

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Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 1800 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • energy derivatives
  • pricing
  • risk management
  • hedging

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Published Papers (2 papers)

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Research

18 pages, 4380 KiB  
Article
Gaussian Process Regression with a Hybrid Risk Measure for Dynamic Risk Management in the Electricity Market
by Abhinav Das and Stephan Schlüter
Risks 2025, 13(1), 13; https://doi.org/10.3390/risks13010013 - 16 Jan 2025
Viewed by 660
Abstract
In this work, we introduce an innovative approach to managing electricity costs within Germany’s evolving energy market, where dynamic tariffs are becoming increasingly normal. In line with recent German governmental policies, particularly the Energiewende (Energy Transition) and European Union directives on clean energy, [...] Read more.
In this work, we introduce an innovative approach to managing electricity costs within Germany’s evolving energy market, where dynamic tariffs are becoming increasingly normal. In line with recent German governmental policies, particularly the Energiewende (Energy Transition) and European Union directives on clean energy, this work introduces a risk management strategy based on a combination of the well-known risk measures of the Value at Risk (VaR) and Conditional Value at Risk (CVaR). The goal is to optimize electricity procurement by forecasting hourly prices over a certain horizon and allocating a fixed budget using the aforementioned measures to minimize the financial risk. To generate price predictions, a Gaussian process regression model is used. The aim of this hybrid approach is to design a model that is easily understandable but allows for a comprehensive evaluation of potential financial exposure. It enables consumers to adjust their consumption patterns or market traders to invest and allows more cost-effective and risk-aware decision-making. The potential of our approach is shown in a case study based on the German market. Moreover, by discussing the political and economical implications, we show how the implementation of our method can contribute to the realization of a sustainable, flexible, and efficient energy market, as outlined in Germany’s Renewable Energy Act. Full article
(This article belongs to the Special Issue Financial Derivatives and Hedging in Energy Markets)
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20 pages, 598 KiB  
Article
Empirical Evidence of the Market Price of Risk for Delivery Periods
by Annika Kemper and Maren Diane Schmeck
Risks 2025, 13(1), 7; https://doi.org/10.3390/risks13010007 - 3 Jan 2025
Viewed by 671
Abstract
In this paper, we provide empirical evidence of the market price of risk for delivery periods (MPDP) of electricity swap contracts. The MPDP enables an accurate pricing of such contracts in the presence of the delivery period such that the typical approximations can [...] Read more.
In this paper, we provide empirical evidence of the market price of risk for delivery periods (MPDP) of electricity swap contracts. The MPDP enables an accurate pricing of such contracts in the presence of the delivery period such that the typical approximations can be avoided. In our empirical study, we focus on term-structure effects and identify the resulting MPDP. In presence of the Samuelson effect, we find the most pronounced MPDP close to maturity, while the MPDP disappears proportional to the Samuelson effect far away from maturity. Thus, our theory improves the pricing accuracy close to maturity. Full article
(This article belongs to the Special Issue Financial Derivatives and Hedging in Energy Markets)
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