Managing Energy Price Risk Using Futures Contracts: A Comparative Analysis (original) (raw)

Energy Commodities: A Review of Optimal Hedging Strategies

Energies, 2019

Energy is considered as a commodity nowadays and continuous access along with price stability is of vital importance for every economic agent worldwide. The aim of the current review paper is to present in detail the two dominant hedging strategies relative to energy portfolios, the Minimum-Variance hedge ratio and the expected utility maximization methodology. The Minimum-Variance hedge ratio approach is by far the most popular in literature as it is less time consuming and computationally demanding; nevertheless by applying the appropriate multivariate model Garch family volatility model, it can provide a very reliable estimation of the optimal hedge ratio. However, this becomes possible at the cost of a rather restrictive assumption for infinite hedger's risk aversion. Within an uncertain worldwide economic climate and a highly volatile energy market, energy producers, retailers and consumers had to become more adaptive and develop the necessary energy risk management and optimal hedging strategies. The estimation gap of an optimal hedge ratio that would be subject to the investor's risk preferences through time is filled by the relatively more complex and sophisticated expected utility maximization methodology. Nevertheless, if hedgers share infinite risk aversion or if alternatively the expected futures price is approximately zero the two methodologies become equivalent. The current review shows that when evidence from the energy market during periods of extremely volatile economic climate is considered, both hypotheses can be violated, hence it becomes reasonable that especially for extended hedging horizons it would be wise for potential hedgers to take into consideration both methodologies in order to build a successful and profitable hedging strategy.

The hedging e¤ectiveness of electricity futures

2008

With the recent popularity of commodity (electricity) and nancial futures, the academic and nancial communities have seen a renewed interest in hedging theories. Hedgers in electricity markets use derivative securities, namely futures, to reduce the risk from variations in the spot market. Hedging aims at reducing the risk involved in holding a nancial asset by taking an exactly o¤setting position, since it reduces the exposure to ‡uctuations in commodity prices. Therefore, the use of weekly and monthly futures contracts as a hedging instrument in 3 European electricity markets [German (EEX), French (Powernext) and Scandinavian (Nord Pool)], is the focus of this research. Weekly spot price risk is hedged with weekly futures for the Nordic Electricity market, month spot risk is hedged with month futures in EEX and Powernext, and we also take into account the fact that futures contracts and spot prices are made distinguishable in these markets. The special features describing elect...

The efficacy of financial futures as a hedging tool in electricity markets

International Journal of Finance & Economics

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). Our key finding is that electricity futures can effectively manage risk only for specific time periods when using hedging strategies that have been very successful in financial and other commodity markets. More generally they are ineffective as a risk management tool when compared with other energy assets. This is especially true at the weekly frequency. We also 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 the Phelix market.

The risk premia of energy futures

Energy Economics, 2021

This paper studies the energy futures risk premia that can be extracted through long-short portfolios that exploit heterogeneities across contracts as regards various characteristics or signals and integrations thereof. Investors can earn a sizeable premium of about 8% and 12% per annum by exploiting the energy futures contract risk associated with the hedgers' net positions and roll-yield characteristics, respectively, in line with predictions from the hedging pressure hypothesis and theory of storage. Simultaneously exploiting various signals towards style-integration with alternative weighting schemes further enhances the premium. In particular, the style-integrated portfolio that equally weights all signals stands out as the most effective. The findings are robust to transaction costs, data mining and sub-period analyses.

Modeling, Risk Assessment and Portfolio Optimization of Energy Futures

This paper examines the portfolio optimization of energy futures by using the STARR ratio that can evaluate the risk and return relationship for skewed distributed returns. We model the price returns for energy futures by using the ARMA(1,1)-GARCH(1,1)-PCA model with stable distributed innovations that reflects the characteristics of energy: mean reversion, heteroskedasticity, seasonality, and spikes. Then, we propose the method for selecting the portfolio of energy futures by maximizing the STARR ratio, what we call "Winner portfolio". The empirical studies by using energy futures of WTI crude oil, heating oil, and natural gas traded on the NYMEX compare the price return models with stable distributed innovations to those with normal ones.

Futures hedging and risk management

2021

This dissertation was written as a part of the MSc in Energy and Finance at the International Hellenic University. Based on the recent literature, on this paper we focus on the effectiveness of different hedging strategies, both constant hedge ratio and time-varying hedge ratio, on natural gas prices in the United States. Natural gas prices fluctuate depending on seasons. To examine how these fluctuations affect the hedging ability of the econometric models we use we conduct an analysis regarding seasons (fall-winter, springsummer) and regarding market conditions (contango-backwardation). The analysis is conducted over different various time horizons (weekly-monthly). We complete this study by presenting the economic-financial benefits of using these hedging strategies in order to assess the impact of volatility in monetary values.

Portfolio optimization of financial commodities with energy futures

Annals of Operations Research

The recent growth in economic and financial markets has brought the focus on energy derivatives as an alternative investment class for investors, financial analysts, and portfolio managers. The financial modeling and risk management of portfolios using the energy derivatives instrument is a requirement and challenge for researchers in the field. The energy and other commodity futures force the expert investors to investigate the broader investment spectrum and consequently diversify their portfolios using the futures instruments. Going beyond the conventional portfolios and developing out-of-the-box strategies that comply with the changing financial and economic advancements are the keys to long-term sustainability in the financial world. This study investigates the impact of diversification with five energy futures from January 2011 to July 2020 on three traditional commodity futures portfolios. The results show that diversification increased the returns while simultaneously reducing the portfolio volatility in all portfolios. The diversified portfolios provided higher returns than the traditional portfolios for the same level of risk. This study also revealed that the results might improve when a short position in the futures contracts is allowed. Moreover, we conclude

Managing market risk in energy

IEEE Transactions on Power Systems, 2003

The market risks encountered by energy asset operators can be categorized as short term/operational, intermediate term/trading, and long term/valuation in nature. This paper describes how the market risks in operations can be measured and managed using real option models and stochastic optimization techniques. It then links these results to intermediate term value at risk and related risk metrics such as cash flow, earnings, and credit risk which can be used to measure trading risks over weeks to months; and how to optimize these portfolios for risk-return relationships. Finally, it then explores the risks in longer term energy portfolio management and how these can be simulated, measured, and optimized. Index Terms-Earnings at risk, energy risk management, portfolio optimization, potential credit exposure, real options, value at risk. Michael Denton, photograph and biography not available at the time of publication.