On the spatial hedging effectiveness of German wind power futures for wind power generators

被引:5
作者
Christensen, Troels Sonderby [1 ,2 ]
Pircalabu, Anca [2 ]
机构
[1] Aalborg Univ, Dept Math Sci, Skjernvej 4A, DK-9220 Aalborg, Denmark
[2] Neas Energy, Quantitat Analyt, Skelagervej 1, DK-9000 Aalborg, Denmark
关键词
wind power generation; wind power futures (WPF); spatial risk; copula models; hedging; tail dependence;
D O I
10.21314/JEM.2018.181
中图分类号
F [经济];
学科分类号
02 ;
摘要
The wind power futures (WPF) recently introduced on the German market fill the gap of a standardized product that directly addresses the volume risk in wind power trading. While, generally speaking, German WPF entail risk-reducing benefits for wind power generators, the extent of these benefits across wind farms with different geographical locations remains unclear. In this paper, we consider the wind utilization in thirty-one different locations in Germany. For each site, we propose a copula model for the joint behavior of the site-specific wind index and the overall German wind index. Our results indicate that static mixture copulas are preferred to the stand-alone copula models usually employed in the economic literature. Further, we find evidence of asymmetric dependence and upper tail dependence. To quantify the benefits of WPF at each wind site, we perform a minimum variance hedge and find that variance reductions can differ greatly depending on the geographical location. Different comparison studies reveal that the presence of (1) a negative risk premium in the WPF market and (2) upper tail dependence weaken the benefits of WPF for wind power generators.
引用
收藏
页码:71 / 96
页数:26
相关论文
共 26 条
[1]   Modeling the multivariate dynamic dependence structure of commodity futures portfolios [J].
Aepli, Matthias D. ;
Fuss, Roland ;
Henriksen, Tom Erik S. ;
Paraschiv, Florentina .
JOURNAL OF COMMODITY MARKETS, 2017, 6 :66-87
[2]   Are benefits from oil-stocks diversification gone? New evidence from a dynamic copula and high frequency data [J].
Avdulaj, Krenar ;
Barunik, Jozef .
ENERGY ECONOMICS, 2015, 51 :31-44
[3]  
Benth F. E., 2017, WORKING PAPER
[4]  
Benth F. E., 2011, INT J STOCHASTIC ANA, V2011, DOI [10.1155/2011/576791, DOI 10.1155/2011/576791]
[5]   Dynamic copula models for the spark spread [J].
Benth, Fred Espen ;
Kettler, Paul C. .
QUANTITATIVE FINANCE, 2011, 11 (03) :407-421
[6]   Analysis and modelling of wind speed in New York [J].
Benth, Jurate Saltyte ;
Benth, Fred Espen .
JOURNAL OF APPLIED STATISTICS, 2010, 37 (06) :893-909
[7]   Copula goodness-of-fit testing: an overview and power comparison [J].
Berg, Daniel .
EUROPEAN JOURNAL OF FINANCE, 2009, 15 (7-8) :675-701
[8]   CROSS-COMMODITY ANALYSIS AND APPLICATIONS TO RISK MANAGEMENT [J].
Boerger, Reik ;
Cartea, Alvaro ;
Kiesel, Ruediger ;
Schindlmayr, Gero .
JOURNAL OF FUTURES MARKETS, 2009, 29 (03) :197-217
[9]  
Christensen T.S., 2017, ESSAYS STOCHASTIC MO, DOI [10.5278/vbn.phd.eng.00027, DOI 10.5278/VBN.PHD.ENG.00027]
[10]   GENERALIZED AUTOREGRESSIVE SCORE MODELS WITH APPLICATIONS [J].
Creal, Drew ;
Koopman, Siem Jan ;
Lucas, Andre .
JOURNAL OF APPLIED ECONOMETRICS, 2013, 28 (05) :777-795