Volatility forecast using hybrid Neural Network models

In this research the testing of a hybrid Neural Networks-GARCH model for volatility forecast is performed in three Latin-American stock exchange indexes from Brazil, Chile and Mexico. A detail of the methodology and application of the volatility forecast of financial series using a hybrid artificial Neural Network model are presented. sults demonstrate that the ANN models can improve the forecasting performance of the GARCH models when studied in the three Latin-American markets and it is shown that the results are robust and consistent for different ANN specifications and different volatility measures.