Heavy-tails and regime-switching in electricity prices

In this paper we first analyze the stylized facts of electricity prices, in particular, the extreme volatility and price spikes which lead to heavy-tailed distributions of price changes. Then we calibrate Markov regime-switching (MRS) models with heavy-tailed components and show that they adequately address the aforementioned characteristics. Contrary to the common belief that electricity price models ‘should be built on log-prices’, we find evidence that modeling the prices themselves is more beneficial and methodologically sound, at least in case of MRS models.Electricity spot price, Heavy-tails, Spikes, Markov regime-switching, Pareto distribution

Heavy-tails and regime-switching in electricity prices

In this paper we first analyze the stylized facts of electricity prices, in particular, the extreme volatility and price spikes which lead to heavy-tailed distributions of price changes. Then we calibrate Markov regime-switching (MRS) models with heavy-tailed components and show that they adequately address the aforementioned characteristics. Contrary to the common belief that electricity price models ‘should be built on log-prices’, we find evidence that modeling the prices themselves is more beneficial and methodologically sound, at least in case of MRS models

Heavy-tails and regime-switching in electricity prices

In this paper we first analyze the stylized facts of electricity prices, in particular, the extreme volatility and price spikes which lead to heavy-tailed distributions of price changes. Then we calibrate Markov regime-switching (MRS) models with heavy-tailed components and show that they adequately address the aforementioned characteristics. Contrary to the common belief that electricity price models ‘should be built on log-prices’, we find evidence that modeling the prices themselves is more beneficial and methodologically sound, at least in case of MRS models

Using Value-at-Risk for effective energy portfolio risk management

It is evident that the prediction of future variance through advanced GARCH type models is essential for an effective energy portfolio risk management. Still it fails to provide a clear view on the specific amount of capital that is at risk on behalf of the investor or any party directly affected by the price fluctuations of specific or multiple energy commodities. Thus, it is necessary for risk managers to make one further step, determining the most robust and effective approach that will enable them to precisely monitor and accurately estimate the portfolio’s Value-at-Risk, which by definition provides a good measure of the total actual amount at stake. Nevertheless, despite the variety of the variance models that have been developed and the relative VaR methodologies, the vast majority of the researchers conclude that there is no model or specific methodology that outperforms all the others. On the contrary, the best approach to minimize risk and accurately forecast the future potential losses is to adopt that specific methodology that will be able to take into consideration the particular characteristic features regarding the trade of energy products

Effective energy commodities’ risk management: Econometric modeling of price volatility

The current study emphasizes on the importance of the development of an effective price risk management strategy regarding energy products, as a result of the high volatility of that particular market. The study provides a thorough investigation of the energy price volatility, through the use of GARCH type model variations and the Markov-Switching GARCH methodology, as they are presented in the most representative academic researches. A large number of GARCH type models are exhibited together with the methodology and all the econometric procedures and tests that are necessary for developing a robust and precise forecasting model regarding energy price volatility. Nevertheless, the present research moves another step forward, in an attempt to cover also the probability of potential shifts in the unconditional variance of the models due to the effect of economic crises and several unexpected geopolitical events into the energy market prices

A structured approach to energy risk management for the South African financial services sector

Energy conservation, efficiency and renewable energy have become a vital part of everyday life and business. The increase in energy cost and the consequences of greenhouse gas emissions necessitates energy management and in particular energy risk management within organisations. Organisations need to manage the possible negative effect that the increased costs will have within the organisation. The present research investigated the introduction of a structured approach to energy risk management within the financial services sector of South Africa. The research followed a quantitative, non-experimental research design by using a structured questionnaire. The questionnaire was sent to managers within the financial services sector. The research investigated the criteria for the implementation of a structured approach to energy risk management such as organisational requirements (culture, corporate social responsibility, management, and finance), governance, energy strategies (energy conservation, efficiency and renewable energy), risk identification, risk management and lastly communication and review. The research found that the structured approach to energy risk management should include the context within the organisation namely organisational requirements, governance and energy strategies. Thereafter the risks within the energy strategies need to be identified, analysed and evaluated, and control measures need to be implemented. It is important to monitor the various energy strategies continuously in order to identify corrections and implement preventative actions. The strategies need to be reviewed and communicated in terms of the various strategies to all stakeholders within the organisation in order to set continual improvement plans. Risk management should form part of the energy management strategies of organisations. The research showed that energy risk management plays an important role in the overall business strategy and that the vast majority of financial services organisations have already implemented some form of energy management. There are however aspects that are still lacking within management strategies that need attention.D. Phil. (Management Studies)Business Managemen