SV mixture models with application to S&P 500 index returns ☆

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Multiple-output support vector regression with a firefly algorithm for interval-valued stock price index forecasting (2014, methodology): “ been used for stock that price forecasting with degrees of success, such as various Box–Jenkins method the [1], general autoregressive conditional heteroskedasticity [2], stochastic volatility model [3], fuzzy logic approach[4], grey -based approaches [5], wavelet transforms and adaptive models [6]”
Forecasting stock indices using radial basis function neural networks optimized by artificial fish swarm algorithm (2011, background): “General Autoregressive Conditional Heteroskedasticity (GARCH) and Stochastic Volatility model (SV) [1].”