Clean energy market connectedness and investment strategies: New evidence from DCC-GARCH R 2 decomposed connectedness measures

被引:8
|
作者
Cocca, Teodoro [1 ]
Gabauer, David [1 ,2 ,3 ]
Pomberger, Stefan [1 ]
机构
[1] Johannes Kepler Univ Linz, Inst Corp Finance, Linz, Austria
[2] LINZ AG, Energy Management, Linz, Austria
[3] Acad Data Sci Finance, Vienna, Austria
关键词
DCC-GARCH; Dynamic connectedness; Contemporaneous connectedness; Dynamic conditional R 2; R; 2; decomposition; Multivariate hedging portfolios; Multivariate minimum risk portfolios; IMPULSE-RESPONSE ANALYSIS; CONDITIONAL HETEROSKEDASTICITY; EFFICIENT TESTS; VOLATILITY; PERFORMANCE; REGRESSION; FUTURES; IMPACT; RETURN; SOLAR;
D O I
10.1016/j.eneco.2024.107680
中图分类号
F [经济];
学科分类号
02 ;
摘要
In this study, we investigate the return propagation mechanism across four clean energy indices, namely, the NASDAQ OMX Green Economy Index, NASDAQ OMX Solar Energy Index, NASDAQ OMX Wind Energy Index, and NASDAQ OMX Geothermal Energy Index ranging from December 21st, 2010 until June 2nd, 2023 by using a novel DCC-GARCH-based R 2 decomposed connectedness approach. This framework allows us to efficiently decompose dynamic conditional R 2 goodness-of-fit measures into its decomposed components. Furthermore, we introduce the concept of minimum R 2 decomposed connectedness portfolios and multivariate hedging portfolios. We find that the dynamic total connectedness is heterogeneous over time and economic-event dependent. In addition, the empirical results highlight that the NASDAQ OMX Green Economy Index is a net transmitter of shocks while all others are net receivers of shocks. Finally, we find that our proposed portfolio technique outperforms the NASDAQ OMX Green Economy Index as well as all alternative multivariate portfolio techniques regarding the hedging effectiveness score and the Sharpe ratio.
引用
收藏
页数:17
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