Publication: Cross-commodity analysis and applications to risk management
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Publication date
2009-03
Defense date
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Publisher
Wiley-Blackwell
Abstract
The understanding of joint asset return distributions is an important ingredient
for managing risks of portfolios. Although this is a well-discussed issue in fixed
income and equity markets, it is a challenge for energy commodities. In this study
we are concerned with describing the joint return distribution of energy-related
commodities futures, namely power, oil, gas, coal, and carbon. The objective of
the study is threefold. First, we conduct a careful analysis of empirical returns
and show how the class of multivariate generalized hyperbolic distributions performs
in this context. Second, we present how risk measures can be computed for
commodity portfolios based on generalized hyperbolic assumptions. And finally,we discuss the implications of our findings for risk management analyzing the
exposure of power plants, which represent typical energy portfolios. Our main
findings are that risk estimates based on a normal distribution in the context of
energy commodities can be statistically improved using generalized hyperbolic
distributions. Those distributions are flexible enough to incorporate many characteristics
of commodity returns and yield more accurate risk estimates. Our
analysis of the market suggests that carbon allowances can be a helpful tool
for controlling the risk exposure of a typical energy portfolio representing a power
plant
Description
Keywords
Commodities, Risk
Bibliographic citation
The Journal of Futures Markets, 2009, v. 29, n. 3, pp. 197-217