TITLE:
Testing and Predicting Volatility Spillover—A Multivariate GJR-GARCH Approach
AUTHORS:
Hira Aftab, Rabiul Alam Beg, Sizhong Sun, Zhangyue Zhou
KEYWORDS:
Asymmetric News, Diversification, Spillovers, Multivariate-t, Chi-Square Test
JOURNAL NAME:
Theoretical Economics Letters,
Vol.9 No.1,
January
29,
2019
ABSTRACT:
This paper proposes a multivariate
VAR-BEKK-GJR-GARCH volatility model to assess the dynamic interdependence among
stock, bond and money market returns and volatility of returns. The proposed
model allows for market interaction which provides useful information for
pricing securities, measuring value-at-risk (VaR), and asset allocation and diversification, assisting financial regulators for
policy implementation. The model is estimated by the maximum likelihood method
with Student-t innovation density. The asymptotic chi-square tests for volatility
spillovers and leverage effects are constructed and provide predictions of
volatility and time-varying correlations of returns. Application of the
proposed model to the Australia’s domestic stock, bond, and money markets
reveals that the domestic financial markets are interdependent and volatility
is predictable. In general, volatility spillovers from stock market to bond and
to money markets due to common news. The empirical findings of this paper
quantify the association among the security markets which can be utilized for
improving agents’ decision-making strategies for risk management, portfolio selection and
diversification.