| Title |
Europos šalių akcijų kainų grąžų analizė ir prognozė / |
| Translation of Title |
European Stocks Returns Analysis And Forecast. |
| Authors |
Mekšunaitė, Erika |
| Full Text |
|
| Pages |
99 |
| Keywords [eng] |
stock exchange ; Google trends ; macroeconomic indicators ; clustering, forecast |
| Abstract [eng] |
Considering the fact that markets are generally influenced by different external factors, the stock market prediction is one of the most difficult tasks of time series analysis. The use of models that provide a reliable prediction in financial time series may to bring valuable profits for the investors, because they can to use the prediction model as a valuable decision support. The European stocks monthly average return prediction model, based on nonlinear autoregressive neural networks and linear regression comparison with partitional and hierarchical clustering comparison for stocks returns time series forecasting is presented in this work. In this way, the prediction was obtained by not just using the previous values of the series but also by using information external to the main series – search engine Google trends and macroeconomic indicators. |
| Dissertation Institution |
Kauno technologijos universitetas. |
| Type |
Master thesis |
| Language |
Lithuanian |
| Publication date |
2017 |
