期刊
ENERGY ECONOMICS
卷 84, 期 -, 页码 -出版社
ELSEVIER
DOI: 10.1016/j.eneco.2019.104536
关键词
Causality; Normalization schemes; Generalized forecast error variance; decomposition; Spillover; Simulation; Vector autoregression models
类别
资金
- Fondazione Cassa di Risparmio di Modena, Italy [FCRM015 IMOM]
- University of Modena
- Reggio Emilia, Italy [FAR16, FAR17, FAR19]
This paper replicates the Diebold and Yilmaz (2012) study on the connectedness of the commodity market and three other financial markets: the stock market, the bond market, and the FX market, based on the Generalized Forecast Error Variance Decomposition, GEFVD. We show that the net spillover indices (of directional connectedness), used to assess the net contribution of one market to overall risk in the system, are sensitive to the normalization scheme applied to the GEFVD. We show that, considering data generating processes characterized by different degrees of persistence and covariance, a scalar-based normalization of the Generalized Forecast Error Variance Decomposition is preferable to the row normalization suggested by Diebold and Yilmaz since it yields net spillovers free of sign and ranking errors. (C) 2019 Elsevier B.V. All rights reserved.
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