The article introduces two new models for analyzing financial data, GHt-GARCH and ODLV-GARCH, which are better at predicting risk than the traditional model. These models take into account skewed and heavy-tailed distributions in the data, which can help investors make more informed decisions. By comparing these new models with the old one using real-world data, the researchers found that both GHt-GARCH and ODLV-GARCH outperform the traditional model. Additionally, a modified version of GHt-GARCH showed even better results for one of the datasets. This research provides valuable insights for improving risk assessment in financial markets.