The aim of this paper is to quantify the strength and the direction of semi-volatility spillovers between five EMU stock markets over the 2000-2016 period. We use upside and downside semi-volatilities as proxies for downside risks and upside opportunities. For this purpose we apply the Diebold and Yilmaz (2012) methodology based on a generalized forecats error variance decomposition, to downside and upside semi-volatility series. While the analysis of Diebold and Yilmaz (2012) is based on a stationary VAR, we take into account the long-memory feature of the series, by using the multivariate extension of the HAR model (VHAR). Moreover, we cast light on how the choice of the normalization scheme can bias the net spillover computation.
Asymmetric semi-volatility spillover effects in EMU stock markets
Francesco Giuseppe Caloia;
2018-01-01
Abstract
The aim of this paper is to quantify the strength and the direction of semi-volatility spillovers between five EMU stock markets over the 2000-2016 period. We use upside and downside semi-volatilities as proxies for downside risks and upside opportunities. For this purpose we apply the Diebold and Yilmaz (2012) methodology based on a generalized forecats error variance decomposition, to downside and upside semi-volatility series. While the analysis of Diebold and Yilmaz (2012) is based on a stationary VAR, we take into account the long-memory feature of the series, by using the multivariate extension of the HAR model (VHAR). Moreover, we cast light on how the choice of the normalization scheme can bias the net spillover computation.File | Dimensione | Formato | |
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