simple and threshold jumps and continuous variation yields a substantial improvement in volatility forecasting or not. The …

variancefunctions. In a genuine out-of-sample forecasting experiment theperformance of the best fitted asMA-asQGARCH model is compared … topure asMA and no-change forecasts. This is done both in terms ofconditional mean forecasting as well as in terms of risk … forecasting. …

forecasting volatility. Key papers in this area include Andersen, Bollerslev, Diebold and Labys (2003), Corsi (2004), Andersen …

The study reports empirical evidence that artificial neural network based models are applicable to forecasting of stock … the artificial neural network based models outperformed the ARIMA based model in forecasting future developments of the … can be used as predictors for forecasting future values of the stock market returns given that the returns has memory of …