This thesis identifies influential characteristics of an energy supplier’s portfolio that determine his decision on hedging. In particular, the influence of portfolio risk and flexibility as well as the influence of portfolio hedge-ability on the hedging decision are being examined. The effects are being controlled for by non-portfolio characteristics that are believed to influence the use of financial derivatives
The applied methodology considers that the data is obtained by repeatedly measuring the figures and ratios on the same companies over time (longitudinal data). The implemented models belong to the class of Generalized Linear Mixed Models (GLMM). With these models a probit regression will be conducted that includes fixed effects as well as random effects.
Statistically significant and stable results have been found for the coherence of FX hedging and portfolio variance. Less stable results have been found for the influence of portfolio variance on commodity hedging.
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This thesis identifies influential characteristics of an energy supplier’s portfolio that determine his decision on hedging. In particular, the influence of portfolio risk and flexibility as well as the influence of portfolio hedge-ability on the hedging decision are being examined. The effects are being controlled for by non-portfolio characteristics that are believed to influence the use of financial derivatives
The applied methodology considers that the data is obtained by repeatedly meas...
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