This study uses the Multiplicative Error Model (MEM) to explore asymmetric volatility spillovers between crude oil and other major asset markets. We have extended the MEM of Engle et al. (2012) and ddd to include asymmetric volatility spillovers and developed the spillover balance as well as...

The paper focused on measuring efficiency of investment strategies and portfolio optimization based on dynamic portfolio formation using the global minimum variance approach in a region of central European countries. The paper analyses DCC GARCH model, which was employed in order to obtain...

This paper investigates market-wide risk aversion in an international setting. Particularly, this empirical study evaluates risk aversion spillover dynamics as an uncertainty transmission mechanism for the period 2000-2015 to reveal if there has been a significant change in these dynamics when...

Using a modified DCC-MIDAS specification that allows the long-term correlation component to be a function of multiple explanatory variables, we show that the stock-bond correlation in the US, the UK, Germany, France, and Italy is mainly driven by inflation and interest rate expectations as well...

This study examines the potential influence of exogenous shocks on time-varying correlations and portfolio strategies between the Asian emerging and other global stock markets including developed and other emerging markets. Using the ARMA-cDCC-FIEGARCH model with and without exogenous shocks,...

This paper aims at contributing to the international portfolio investment decisions among the emerging BRICS countries where individual and institutional investors seek diversification benefits and to help in advocating policy changes and implementation as a response to the changing dynamics in...

We introduce a methodology for dynamic modelling and forecasting of realized covariance matrices based on generalization of the heterogeneous autoregressive model (HAR) for realized volatility. Multivariate extensions of popular HAR framework leave substantial information unmodeled in residuals....

Using a modified DCC-MIDAS specification that allows the long-term correlation component to be a function of multiple explanatory variables, we show that the stock-bond correlation in the US, the UK, Germany, France, and Italy is mainly driven by inflation and interest rate expectations as well...

This study investigates the factors of Bitcoin's tail risk, quantified by Value at Risk (VaR). Extending the conditional autoregressive VaR model proposed by Engle and Manganelli (2004), I examine 30 potential drivers of Bitcoin's 5% and 1% VaR. For the 5% VaR, quantity variables, such as...