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 risk and upside opportunities. In this way, we aim to complement the literature, which has focused mainly on the contemporaneous correlation between positive and negative returns, with the evidence of asymmetry also in semi-volatility transmission. For this purpose, we apply the Diebold and Yilmaz (2012) methodology, based on a generalized forecast error variance decomposition, to downside and upside realized semi-volatility series. While the analysis of Diebold and Yilmaz (2012) is based on a stationary VAR, we take into account the long-memory behaviour of the series, by using the multivariate extension of the HAR model (named VHAR model). Moreover, we cast light on how the choice of the normalization scheme can bias the net-spillover computation in a full sample as well as in a rolling sample analysis.
Original language | English |
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Pages (from-to) | 221-230 |
Number of pages | 10 |
Journal | International Review of Financial Analysis |
Volume | 57 |
Early online date | 20 Mar 2018 |
DOIs | |
Publication status | Published - May 2018 |
Funding
S. Muzzioli gratefully acknowledges financial support from Fondazione Cassa di Risparmio di Modena , for the project “Volatility and higher order moments: new measures and indices of financial connectedness” ( 2015.0333 ) and from the FAR2015 project “A SKEWness index for Europe (EU-SKEW)”.
Funders | Funder number |
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EU-SKEW | |
SKEWness index for Europe | |
Fondazione Cassa di Risparmio di Modena | 2015.0333 |
Keywords
- Asymmetry
- Forecast error variance decomposition
- Semi-volatility
- Spillover
- VHAR