Predicting Stock Index Volatility Using Artificial Neural Networks: An empirical study of the OMXS30, FTSE100 & S&P/ASX200
In this thesis I study the performances of artificial neural networks (ANNs) and three various ARCH-type models to predict weekly volatility of the Swedish (OMXS30), the British (FTSE100) and the Australian (S&P/ASX200) major stock indices. The three various ARCH-type models are the GARCH(1,1), the EGARCH(1,1) and the TGARCH(1,1). The purpose is to investigate if ANNs outperform the more tradi