MGARCH models: Trade-off between feasibility and flexibility

Multivariate GARCH (MGARCH) models need to be restricted so that their estimation is feasible in large systems and so that the covariance stationarity and positive definiteness of conditional covariance matrices are guaranteed. This paper analyzes the limitations of some of the popular restricted parametric MGARCH models that are often used to represent the dynamics observed in real systems of financial returns. These limitations are illustrated using simulated data generated by general VECH models of different dimensions in which volatilities and correlations are interrelated. We show that the restrictions imposed by the BEKK model are very unrealistic, generating potentially misleading forecasts of conditional correlations. On the other hand, models based on the DCC specification provide appropriate forecasts. Alternative estimators of the parameters are important in order to simplify the computations, and do not have implications for the estimates of conditional correlations. The implications of the restrictions imposed by the different specifications of MGARCH models considered are illustrated by forecasting the volatilities and correlations of a five-dimensional system of exchange rate returns.     

Shock and volatility spillovers among equity sectors of the Gulf Arab stock markets

The major objectives of this study are twofold. The first objective is to examine the dynamic volatility and volatility transmission in a multivariate setting using the VAR(1)–GARCH(1,1) model for three major sectors, namely, Service, Banking and Industrial/or Insurance, in four Gulf Cooperation Council (GCC)’s economies (Kuwait, Qatar, Saudi Arabia and UAE). The second is to use the models’ results to compute and analyze the optimal weights and hedge ratios for two-sector portfolio holdings, comprised of the three sectors for each country. The results suggest that past own volatilities matter more than past shocks and there are moderate volatility spillovers between the sectors within the individual countries, with the exception of Qatar. Moreover, the values for ratios of hedging long positions with short positions in the GCC sectors are smaller than those for the US equity sectors. The optimal portfolio weights favor the Banking/financial sector for Qatar, Saudi Arabia and UAE and the Industrial sector for Kuwait.     

Market integration between conventional and Islamic stock prices

The paper assesses the market integration between conventional and Islamic stock prices from the long- and short-run perspectives for France, Indonesia, the UK and the US from September 8, 2008 to September 6, 2013 using various econometric approaches. The results show long-run relationships for all countries, except for the UK where there is no cointegration between conventional and Islamic stock prices. These findings suggest that the Islamic finance industry in the considered economies (except the UK) does not seem to be compliant to Islamic law's maxims, which hinders portfolio managers and market participants to benefit from the opportunities of international diversification and hedging effectiveness. From the correlation perspective, there is evidence of weak linkages between the Indonesian market and the developed markets for both conventional and Islamic stock prices, thus suggesting that investors can diversify their portfolios at the international level to minimize risk. However, there is high connection between the developed markets for both conventional and Islamic indexes. In addition, for each economy, the Islamic index is found to be strongly linked with its conventional counterpart. The structural change analysis reveals common break dates for several cross correlations, thus reflecting the similar time-paths of the interactions between markets. The presence of breaks in the inter-market linkages has important implications for international investors as regards portfolio diversification benefits and for financial policy makers regarding contagion risks and market policies.     

The outbreak of COVID-19 and stock market liquidity: Evidence from emerging and developed equity markets

The outbreak of the novel corona virus has heightened concerns surrounding the adverse financial effects of the outbreak on stock market liquidity and economic policies. This paper contributes to the emerging strand of studies examining the adverse effects of the virus on varied aspect of global markets. The paper examines the causality and co-movements between COVID-19 and the aggregate stock market liquidity of China, Australia and the G7 countries (Canada, France, Italy, Japan, Germany, the UK and the US), using daily three liquidity proxies (Amihud, Spread and Traded Value) over the period December 2019 to July 2020. Our empirical analysis encompasses wavelet coherence and phase-differences as well as a linear Granger causality test. Linear causality test results suggest that a causal relationship exists between the number of cases of COVID 19 infections and stock market liquidity. To quantitatively examine the degree of causality between COVID-19 outbreak and stock market liquidity, we employ the continuous wavelet coherence approach with results revealing the unprecedented impact of COVID-19 on stock market liquidity during the low frequency bands for countries that were hard hit with the COVID-19 outbreak, i.e., Italy, Germany, France, the UK and the US. Further, evidence shows that there is a heterogeneous lead-lag nexus across scales for the entire period of the study.