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.

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.

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.

Keywords: forecasting, risk management
Published in: Global Energy Business
Publication year: 2002
Co-Author 1: Richard Hooke


In competitive markets, all customers must be pursued, but all customers are not alike. Some bring more risk than reward to a marketer’s overall portfolio. Profitability demands that marketers price these hidden risks appropriately.

Keywords:
Published in:
Publication year: 2000
Co-Author 1:  Donald F. Larson

This study tested for the presence of risk premiums on crude oil and natural gas. The econometric analysis followed from a stochastic model in which the equilibrium value of inventories depends on a convenience yield and an option value related to price uncertainty. The empirical findings provide rather strong support for the presence of risk premiums and also evidence for the existence of convenience yields. The risk premiums rose sharply with greater price volatility and help to explain why prices for immediate sales often exceed prices for future delivery.

Keywords: weather, risk
Published in: Weather
Publication year: 2004

Energy Risk’s inaugural weather derivatives survey shows that traders and end-users appear to be confident about the state of their business, despite high-profile exits from the industry in recent years.

Keywords:
Published in:
Puclication year: 2000
Co-author 1: Chris Strickland
Co-author 2: Vince Kaminski

Value-at-Risk (VaR) is a widely relied upon method of calculating risk in the energy industry. But which approach is the most accurate?

Keywords:
Published in: The McKinsey Quarterly
Publication year: 2000
Co-author 1: Keith Leslie

In following a penchant to diversify, European utilities risk biting off more than they can chew. Eventually, they will probably find themselves paring down their asset base as quickly as they are now enlarging it.

Keywords: Tradable Green Certificates, Financial Risk, Forward Contracts
Published in: 
Publication year: 

This paper analyzes financial risks in a market for Tradable Green Certificates (TGC), both from the perspective of existing renewable producers and potential investors in new renewable electricity generation capacity. The pricing mechanism for a consumer-based TGC market with perfect competition is described. A TGC system with wind turbines as the sole technology is analyzed. In this framework production from wind turbines and TGC prices will be negatively correlated, implying that a distinction between revenue and price fluctuations is important. Finally analytical expressions for revenue-variance-minimizing trading strategies are derived and an analysis of the demand and supply for financial hedging show that forward contracts will be traded at a risk premium.

Keywords: Risk management; State price density; Unique Martingale measure; Complete markets; Option pricing
Published in: Journal of financial economics
Publication year: 2001
Co-author 1: Helyette Geman
Co-author 2: Dilip B. Madan

We present a new approach for positioning, pricing, and hedging in incomplete markets that bridges standard arbitrage pricing and expected utility maximization. Our approach for determining whether an investor should undertake a particular position involves specifying a set of probability measures and associated floors which expected payoffs must exceed in order for the investor to consider the hedged and financed investment to be acceptable. By assuming that the liquid assets are priced so that each portfolio of assets has negative expected return under at least one measure, we derive a counterpart to the first fundamental theorem of asset pricing. We also derive a counterpart to the second fundamental theorem, which leads to unique derivative security pricing and hedging even though markets are incomplete. For products that are not spanned by the liquid assets of the economy, we show how our methodology provides more realistic bid–ask spreads. r 2001 Published by Elsevier Science S.A.