A comparison between Fama and French's model and artificial neural networks in predicting the Chinese stock market

2005 ◽  
Vol 32 (10) ◽  
pp. 2499-2512 ◽  
Author(s):  
Qing Cao ◽  
Karyl B. Leggio ◽  
Marc J. Schniederjans
Keyword(s):  
Neural Networks ◽  
Artificial Neural Networks ◽  
Stock Market ◽  
Chinese Stock Market ◽  
Artificial Neural

scholarly journals Analysis of ARIMA-Artificial Neural Network Hybrid Model in Forecasting of Stock Market Returns

2020 ◽  
pp. 42-53
Author(s):  
Yakubu Musa ◽  
Stephen Joshua
Keyword(s):  
Neural Network ◽  
Neural Networks ◽  
Artificial Neural Network ◽  
Artificial Neural Networks ◽  
Stock Market ◽  
Hybrid Model ◽  
Market Returns ◽  
Stock Market Returns ◽  
Artificial Neural ◽  
Modelling And Forecasting

This study focuses on the modelling of Nigerian stock market all–shares index and evaluations of predictions ability using ARIMA, Artificial Neural Network and a hybrid ARIMA-Artificial Neural Network model. The ARIMA (1,1,1) model and neural network with architecture (6:1:3) turns out to be the most fitted among the considered models, these models were used for forecasting the returns, and their performances have been compared according to some statistical measure of accuracy. A hybrid model has been constructed using ARIMA-Artificial Neural Networks model, the computational results on the data reveal that the hybrid model using Artificial Neural Network, provides better forecasts, and will enhance forecasting over the single ARIMA and Artificial Neural Networks models. The study recommends the use of ARIMA-Artificial neural network for modelling and forecasting stock market returns.

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