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Portfolio and Security Analysis

Technological University Dublin

Series

Energy

Publication Year

Articles 1 - 3 of 3

Full-Text Articles in Business

Volatility And Risk Management In European Electricity Futures Markets, Jim Hanly, Lucia Morales May 2015

Volatility And Risk Management In European Electricity Futures Markets, Jim Hanly, Lucia Morales

Articles

This paper estimates and applies a risk management strategy for electricity spot exposures using futures hedging. We apply our approach to three of the most actively traded European electricity markets, Nordpool, APXUK and Phelix. We compare both optimal hedging strategies and the hedging effectiveness of these markets for two hedging horizons, weekly and monthly using both Variance and Value at Risk (VaR). We find significant differences in both the Optimal Hedge Ratios (OHR’s) and the hedging effectiveness of the different electricity markets. Better performance is found for the Nordpool market while the poorest performer in hedging terms is Phelix. However …


Performance Of Utility Based Hedges, Jim Hanly, John Cotter Jan 2015

Performance Of Utility Based Hedges, Jim Hanly, John Cotter

Articles

Hedgers as investors are concerned with both risk and return. However when measuring hedging performance, the role of returns and investor risk aversion has generally been neglected in the literature, by its focus on minimum variance hedging. In this paper we address this by using utility based performance metrics to evaluate the hedging effectiveness of utility based hedges for hedgers with both moderate and high risk aversion together with the more traditional minimum variance approach. To examine this for an energy hedger, we apply our approach to WTI Crude Oil, for three different hedging horizons, daily, weekly and monthly. We …


Time Varying Risk Aversion: An Application To Energy Hedging, Jim Hanly, John Cotter Jan 2010

Time Varying Risk Aversion: An Application To Energy Hedging, Jim Hanly, John Cotter

Articles

Risk aversion is a key element of utility maximizing hedge strategies; however, it has typically been assigned an arbitrary value in the literature. This paper instead applies a GARCH-in-Mean (GARCH-M) model to estimate a time-varying measure of risk aversion that is based on the observed risk preferences of energy hedging market participants. The resulting estimates are applied to derive explicit risk aversion based optimal hedge strategies for both short and long hedgers. Out-of-sample results are also presented based on a unique approach that allows us to forecast risk aversion, thereby estimating hedge strategies that address the potential future needs of …