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.

Caloia, F.G., Cipollini, A., & Muzzioli, S. (2018). Asymmetric semi-volatility spillover effects in EMU stock markets. INTERNATIONAL REVIEW OF FINANCIAL ANALYSIS, 57, 221-230 [10.1016/j.irfa.2018.03.001].

Asymmetric semi-volatility spillover effects in EMU stock markets

Cipollini, Andrea;
2018

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.
Caloia, F.G., Cipollini, A., & Muzzioli, S. (2018). Asymmetric semi-volatility spillover effects in EMU stock markets. INTERNATIONAL REVIEW OF FINANCIAL ANALYSIS, 57, 221-230 [10.1016/j.irfa.2018.03.001].
File in questo prodotto:
File Dimensione Formato  
Asymmetric semi-volatility spillover effects in EMU stock markets.pdf

Solo gestori archvio

Tipologia: Versione Editoriale
Dimensione 2.87 MB
Formato Adobe PDF
2.87 MB Adobe PDF   Visualizza/Apri   Richiedi una copia

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/10447/288502
Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus 18
  • ???jsp.display-item.citation.isi??? 17
social impact