using the GARCH-M model. A sample is collected by clustering daily closing and opening prices from the official websites of … when using the GARCH-M model, which indicates pharma stock volatility clustering before the COVID-19 pandemic, that a … through effective prediction based on time-series analysis. The GARCH-M model is compatible with predicting future stock price …

asymmetric GARCH-M (EGARCH-M, TGARCH-M, and PGARCH-M) were further applied. The findings from different versions of the ARDL(p,q1 …

asymmetric GARCH-M (EGARCH-M, TGARCH-M, and PGARCH-M) were further applied. The findings from different versions of the ARDL(p,q1 …

interrelationships between Visegrad fuel markets. Additionally, the paper uses multivariate dynamic conditional GARCH (DCC GARCH-M …

investment decisions. The used risk attribution quantification models GARCH (1.1), EGARCH (1.1), GARCH-M (1.1) and TGARCH (1 … models GARCH, EGARCH, GARCH-M and TGARCH with specification (1.1). The research covers the net balance sheet value of forty … of the models GARCH, EGARCH and GARCH-M with the highest risk concentration the investment fund "Golden Lev Index 30 …

interrelationships between Visegrad fuel markets. Additionally, the paper uses multivariate dynamic conditional GARCH (DCC GARCH-M …

any dynamic link between risk and return in the Indian fintech market. The variance-based Mean-GARCH (GARCH-M) model was …