Abstract
Time Series Forecasting of the Austrian Traded Index (ATX) Using Artificial Neural Network Model
Highlights
The artificial neural network (ANN) is a popular nonlinear concept often used in time series forecasting
Sampling data are taken from the web page of the Wiener Börse and filtered on weekly basis to comply with weekly seasonality in eight years range
The casual methods work on behalf of input explanatory variables that are deemed as important impact or for predicted variable, while time series methods capturing underlying pattern using solely datasets of the previous observations, make it very simple to analyse and study
Summary
The artificial neural network (ANN) is a popular nonlinear concept often used in time series forecasting. The casual methods work on behalf of input explanatory variables that are deemed as important impact or for predicted variable, while time series methods capturing underlying pattern using solely datasets of the previous observations, make it very simple to analyse and study. They are not restricted to need to know underlying nature of neither generated data nor important factors that can influence the outcome. Marko MARTINOVIĆ et al.: Time Series Forecasting of the Austrian Traded Index (ATX) Using Artificial Neural Network Model optimal solution if real data characteristics do not match model assumptions. Prediction was made using standard econometric methods and feed forward neural networks
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