The rapid growth of BRICS has increasingly integrated their markets into the global economy. Thus, making their financial markets more vulnerable to external shocks such as global economic policy uncertainties. In this light, this study examines BRICS stock markets’ response to global economic...

This study proposes a GARCH copula quantile regression model to capture the downside and upside tail dependence between oil price change and stock market returns at different risk levels. In the model, ten copulas are provided to measure the nonlinearity of the tail dependence with the marginal...

We propose a new clustering approach for comparing financial time series and employ it to study how the COVID-19 pandemic affected the U.S. stock market. Essentially, we compute the forecast accuracy of asymmetric GARCH models applied to S&P500 industries and use the model forecast errors for...

We investigate whether range-based estimators contain information in forecasting realized volatility within a HAR-RV-X framework and applied to G7 stock markets. Using a rolling window approach and QLIKE, HMSE and MCS forecast criteria, overall findings suggest that while no single model...

This paper proposes a novel extension of log and exponential GARCH models, where time-varying parameters are approximated by orthogonal polynomial systems. These expansions enable us to add and study the effects of market-wide and external international shocks on the volatility forecasts and...

This investigation utilized the VARX-DCC-MEGARCH model assimilated with skewed-t density to analyze the time-different (i.e., daytime, overnight, and daily) connectedness among S&P 500, DAX 30, FTSE-100, Nikkei 225, and Shanghai Composite Index. This investigation discovered that the current...

Evidence that cryptocurrencies exhibit speculative bubble behavior is well documented. This evidence could trigger global financial instability leading to systemic risk. It is therefore crucial to quantify systemic risk and investigate its transmission mechanism across crypto markets and other...

This study explores the stylized facts, volatility clustering, other highly irregular behaviour, and risk measures of cryptocurrencies' returns. By analysing bitcoin, ripple, and ethereum daily data we establish evidence of strong dependencies among analysed cryptocurrencies. This paper provides...