generalized autoregressive conditional heteroscedasticity (GARCH) models are applied. Macroeconomic shocks (GDP, ZEW, IFO, factory … volatility during the 7-year total examined time period. Splitting the time series into 3 individual sub-periods the results … conditional volatility during financial crises. Furthermore, announcements of GDP and ZEW index calm the exchange rate …

exponential GARCH (EGARCH) model with an integrated dynamic conditional correlation (DCC) approach to measure the impact on the …This research examines the correlations between the return volatility of cryptocurrencies, global stock market indices …, and the spillover effects of the COVID-19 pandemic. For this purpose, we employed a two-stage multivariate volatility …

-19 pandemic. We applied the GARCH (1, 1), GJR-GARCH (1, 1), and EGARCH (1, 1) econometric models on the daily time series … the market volatility and asymmetric behavior of Bitcoin, EUR, S&P 500 index, Gold, Crude Oil, and Sugar during the COVID … returns data ranging from 27 November 2018 to 15 June 2021. The empirical findings show a high level of volatility persistence …

, the Johansen-Juselius cointegration test, generalized autoregressive conditional heteroskedasticity (GARCH) model …, exponential generalized autoregressive conditional heteroskedasticity (EGARCH) model, variance decomposition method, and impulse …. We find a significant effect of oil price volatility on the stock market in both sub-periods from the GARCH model …