This study examines how the relationship between oil and stock market return of BRICS behaves at different investment horizons. Using data ranging from 2006 to 2020, wavelet MGARCH-DCC found that markets’ Russia, Brazil, South Africa are comparatively more correlated with price across horizons volatile particularly during Covid-19 period. However, China India is less volatile. It also revealed ...

This study analyzes the volatility spillover effects in US stock market (S&P500) and cryptocurrency (BGCI) using intraday data during COVID-19 pandemic. As potential drivers of portfolio diversification, we measure asymmetric transmission on both markets. We apply MGARCH-BEKK algorithm-based GA2M machine learning model. The negative shocks to returns impact S&P500 more than positive als...

This paper examines the transmission of equity returns and volatility among Asian equity markets and investigates the differences that exist in this regard between the developed and emerging markets. Three developed markets (Hong Kong, Japan and Singapore) and six emerging markets (Indonesia, Korea, Malaysia, the Philippines, Taiwan and Thailand) are included in the analysis. A multivariate gen...

This study provides cross country robust evidence on interdependencies among inflation, output growth and respective uncertainties for the current era of low inflation policies. We attribute the extant empirical disagreement on these relations to the fact that long sampling periods and single economies are typically considered for analysis. In this study, VARX-MGARCH-M models are estimated for ...

This paper is focused on examining the number of deaths' increases participation in the propagating the Ebola virus during the period ranging from March to October 2014. An application of the MGARCH-DCC model regressions on four countries has led to discover that the finding that human contact play a significant role in transmitting the Ebola virus. Our findings also reveal that Guinea has alre...

The analysis of causality among oil prices and, in general, between financial and economic variables is central relevance applied studies. recent contribution Lu et al. (2014) proposes a new test, the DCC-MGARCH Hong test. We show that critical values test statistic should be evaluated through simulations to avoid potential Type I errors. also note rolling tests represent more viable solution p...

Volatility and investor sentiment have been factors for the slow adoption rate of Bitcoin (BTC) that was first recognized in 2008 as a potential store value, investment vehicle hedge alternative to gold during recession. The purpose this applied mathematics study will use multivariate DCC GARCH model. holds its ground volatility. This examines an well major stock index. To perform research expl...

We analyse the determinants of stock market integration among EU member states for the period 1999–2007. First, we apply bivariate DCC-MGARCH models to extract dynamic conditional correlations between European stock markets, which are then explained by interest rate spreads, exchange rate risk, market capitalisation, and business cycle synchronisation in a pooled OLS model. By grouping the coun...

We investigate conditional correlations between six CEEC-3 financial markets estimated by DCC-MGARCH models. In general, the highest correlations exist between Hungary and Poland in foreign exchange and stock markets. Short-term money markets are rather isolated from each other. We find that the associations of CEEC-3 exchange rates versus the euro are weaker than those versus the US dollar. Th...