"Serving the energy market" - Articles - Risk management

Modelling dependence of extreme events in energy markets using tail copulas

no@spam.com (Sergej Obžigailov) — Tue, 13 Dec 2011 14:05:39 CET

Co-Author 1: Stefan Jäschke (RWE Supply & Trading GmbH)
Co-Author 2: Karl Friedrich Siburg (Fakultät für Mathematik TU Dortmund)
Co-Author 3: Pavel A. Stoimenov (Fakultät Statistik TU Dortmund)

Abstract
This paper studies the dependence of extreme events in energy markets. Based on a large data set comprising quotes of crude oil and natural gas futures, large co-movements of commodity returns are estimated and modeled. To detect the presence of tail dependence a new method based on the concept of tail copulas which accounts for different scenarios of joint extreme outcomes is applied. Moreover, it is shown that the common practice to fit copulas to the data cannot capture the dynamics in the tail of the joint distribution and, therefore, is unsuitable for risk management purposes.

Portfolio optimization in electricity markets

no@spam.com (Min Liu) — Tue, 11 Aug 2009 16:16:13 CEST

Published in: Electrical power systems research

Publication year: 2006
Co-Author 1: Felix Wu

In a competitive electricity market, Generation companies (Gencos) face price risk and delivery risk that affect their profitability. Risk management is an important and essential part in the Genco’s decision making. In this paper, risk management through diversification is considered. The problem of energy allocation between spot markets and bilateral contracts is formulated as a general portfolio optimization problem with a risk-free asset and n risky assets. Historical data of the PJM electricity market are used to demonstrate the approach.

Multiple zone power forwards

no@spam.com (Jean-Guy Demers) — Fri, 07 Aug 2009 17:43:47 CEST

Published in: Energy Economics
Publication year:2009

Over the 1990s, deregulated power markets in New-England provided zones with fluctuating spot prices. Such prices have a notoriously high volatility, owing to the difficulty of storing electrical energy and the delays needed to adjust generation levels. In this context, forward contracts have become increasingly popular and understanding their dynamic is a problem facing many market players.

This paper proposes a parsimonious parametric model, based on the price series of all n-month forward contracts (n=1,2,3…), encompassing multiple zones. The model is then used for value at risk forecasts, which are backtested and compared with the ones in use by the risk management unit of an important electricity producer. Extensions

to include natural gas and power-relevant oil-based future markets are discussed.

Volunteering to fight global warming

no@spam.com (Anne Ku) — Sat, 29 Dec 2007 14:13:08 CET

Keywords:
Published in: Global Energy Business
Publication year: 2001

Most energy companies know that governments will—sooner or later—impose limits on their emissions of greenhouse gases. A small but growing number— including two oil majors and some big U.S. utilities—are already preparing for the inevitable. They are taking voluntary steps to reduce the amounts of CO2 and pollutants their activities generate, and experimenting with market-based and internal programs for trading emissions credits for multiple greenhouse gases. Such proactive approaches do more than lend needed certainty to corporate environmental planning; they also promise to give their ‘green’ adopters a competitive edge, in the form of early practical experience with emissions measurement and trading and compliance risk management.

Electricity price modelling for profit at risk management

no@spam.com (Jacob Lemming) — Fri, 21 Dec 2007 14:12:52 CET

Keywords:
Published in:
Publication year:

In liberalized electricity markets power producers face a wide range of decision problems that require modelling of electricity prices as a crucial input. In this chapter we look at risk management decisions and specifically on how electricity price modelling affects the optimal solution to a relatively simple risk management decision problem

Pieces of Power

no@spam.com (Alain McNee) — Mon, 17 Dec 2007 15:01:58 CET

Keywords:
Published in: Erisk
Publication year: 2001

The gap between market risk management and the risk management of major assets is slowly closing in the energy markets, with implications for enterprise risk management.

A Multi-Factor Model for Energy Derivatives

no@spam.com (Chris Strickland) — Mon, 03 Dec 2007 17:42:49 CET

Keywords:
Published in:
Publication year: 1999
Co-author 1: Les Clewlow

In this paper we develop a general framework for the risk management of energy derivatives. The framework is designed to be consistent not only with the market observable forward price curve but also the volatilities and correlations of forward prices. We show how these volatilities and correlations can be estimated from the market and incorporated into the model in order to price a wide range of energy derivatives. Our framework extends and synthesises the results of Amin and Jarrow [1991a,b], Cortazar and Schwartz [1994], Amin, Ng and Pirrong [1995], Schwartz [1997], and Hilliard and Reis [1998]. We demonstrate the application of our framework to oil and gas futures data from the New York Mercantile Exchange and give numerical results for the pricing of European Caps and Swaptions.

Risk management in a large rural electrification programme

no@spam.com (Subhes C. Bhattacharyya) — Thu, 01 Nov 2007 15:36:10 CET

Keywords: Rural electrification, risk identification, risk mapping, risk mitigation.
Published in:
Publication year: 2005
Co-author 1: Prasanta K. Dey

Although rural electrification projects and programs have been implemented in many countries, they suffered from design, planning, implementation and operational flaws. This paper presents a risk management framework in order to manage large scale development projects effectively. The proposed framework first identifies, with the involvement of the stakeholders, the risk factors of a rural electrification programme at three different levels. Subsequently it develops a qualitative risk prioritizing scheme through probability and severity mapping and provides mitigating measures for most vulnerable risks. The study concludes that the hierarchical risk management approach provides an effective framework for managing large-scale rural electrification program.

Managing the spark spread

no@spam.com (Cyriel de Jong) — Thu, 01 Nov 2007 11:58:35 CET

Keywords: power plant, real options, spark spread, hedging, valuation, optimal operation
Pulished in:
Publication year: 2003

In this paper we describe the decision problem of the manager of a power plant. The plant manager needs to decide on the production levels of the facility based on current and future spark spreads and production costs. Furthermore, decisions need to be made on the optimal hedging strategy with tradable financial contracts in the electricity output and the input fuel. We show that optimal production decisions and optimal financial contracting decisions depend largely on the flexibility with which the facility can be operated, and thus on the level of volatility that may be exploited. On one side of the spectrum, so-called baseload plants will be generating power almost continuously, and hedging financial risks is done with tradable long-term forward contracts, which yields a direct value based on option theory (Margrabe, 1978). On the other side of the spectrum, so-called peaking plants will be generating power only in short periods of high demand, and hedging financial risks is only possible to a very limited extent, since financial contracts on future short-term delivery periods are barely traded. As long as the risk preferences of the plant owner are taken into account, real option valuation and optimal operating decisions can however be obtained for peaking plants by simulating the appropriate market prices in combination with the least squares Monte Carlo simulation approach (Carriere, 1996; Longstaff and Schwartz, 2001).

To store or not to store

no@spam.com (Cyriel de Jong) — Thu, 01 Nov 2007 11:40:55 CET

Keywords:
Published in: Energy Risk
Publication year: 2003

Here we describe the optimal operation and valuation of gas storage based on a real option methodology. Using Zeebrugge gas prices as a practical example, Cyriel de Jong clarifies the optionality in gas storage, analyse its valuation and discuss hedging strategies to secure part of the storage value