Abstract
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.
Original language | English |
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Article number | 104536 |
Pages (from-to) | 1-13 |
Number of pages | 13 |
Journal | Energy Economics |
Volume | 84 |
Early online date | 23 Oct 2019 |
DOIs | |
Publication status | Published - Oct 2019 |
Funding
The authors wish to thank the editor and three anonymous referees for their comments and suggestions. The usual disclaimer applies. This work was supported by Fondazione Cassa di Risparmio di Modena , Italy, FCRMO15 IMOM, University of Modena and Reggio Emilia , Italy, FAR16, FAR17, FAR19. Appendix A
Funders | Funder number |
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Fondazione Cassa di Risparmio di Modena | |
Università Degli Studi di Modena e Reggio Emila | FAR19 |
Keywords
- Causality
- Generalized forecast error variance decomposition
- Normalization schemes
- Simulation
- Spillover
- Vector autoregression models