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Short and long-term forecasting using artificial neural networks for stock prices in Palestine: a comparative study
(2017)
To compare the forecast accuracy, Artificial Neural Networks, Autoregressive Integrated Moving Average and regression models were fit with training data sets and then used to forecast prices in a test set. Three different ...
The efficiency of artificial neural networks for forecasting in the presence of autocorrelated disturbances
(2016)
We compare three forecasting methods, Artificial Neural Networks (ANNs), Autoregressive Integrated Moving Average (ARIMA) and Regression models. Using computer simulations, the major finding reveals that in the presence ...
The efficiency of OLS in the presence of auto-correlated disturbances in regression models
(2006)
The ordinary least squares (OLS) estimates in the regression model are efficient when the disturbances have mean zero, constant variance, and are uncorrelated. In problems concerning time series, it is often the case that ...