Liberalised Energy Markets — Do We Need Re-Regulation?

This chapter discusses the role of energy in economic development, the transformation of energy markets, trade in energy resources themselves, and the geopolitical dynamics that result. The transformation of energy markets and their expansion via trade can help or hinder development, depending on the processes behind them and how stakeholders interact. The availability of renewable, climate-friendly sources of energy, domestically and internationally, means that there is no inherent trade-off between economic growth and the use of fossil fuels. The existence of economic, political, social, and geopolitical adjustment costs means that the expansion of international energy markets to incorporate alternatives to oil and coal is a complex balance of environmental trade-offs with no solutions completely free of negative impact risk. An understanding of the supply of and demand for energy must incorporate the institutional context within which they occur, as well as the social and political dynamics of their setting.

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Dependence Modeling in Energy Markets using Sibuya-type Copulas

International Journal of Statistics and Probability ◽

10.5539/ijsp.v6n3p43 ◽

2017 ◽

Vol 6 (3) ◽

pp. 43

Author(s):

Nikolai Kolev ◽

Jayme Pinto

Keyword(s):

Goodness Of Fit ◽

Basic Assumption ◽

Energy Markets ◽

Dependence Structure ◽

Dependence Function ◽

Dependence Modeling ◽

Goodness Of Fit Tests ◽

Oil And Natural Gas ◽

Error Terms ◽

Time Invariant

The dependence structure between 756 prices for futures on crude oil and natural gas traded on NYMEX is analyzed using a combination of novel time-series and copula tools. We model the log-returns on each commodity individually by Generalized Autoregressive Score models and account for dependence between them by fitting various copulas to corresponding error terms. Our basic assumption is that the dependence structure may vary over time, but the ratio between the joint distribution of error terms and the product of marginal distributions (e.g., Sibuya's dependence function) remains the same, being time-invariant. By performing conventional goodness-of-fit tests, we select the best copula, being member of the currently introduced class of Sibuya-type copulas.

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