The SWGARCH model is a new and improved version of the popular GARCH model for forecasting time series data. It uses a sliding window technique to estimate variance, which helps make predictions more accurate. When tested on real stock market data, SWGARCH outperformed both the original GARCH model and another common forecasting model called ARIMA-GARCH. This means that SWGARCH is a better option for predicting future trends in financial markets.