Akcijų kainų ARIMA ir LSTM prognozavimo metodųlyginamoji analizė
In the work, relevant methods of stock price forecasting are applied and compared: statistical time series (ARIMA, SARIMA) and neural network-based (LSTM). The results of stock price (Ama- zon, Apple, Google, Netflix, and Tesla companies) simulations are evaluated using MAE and MRE measures. The con...
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| Izdano u: | Lietuvos matematikos rinkinys |
|---|---|
| Glavni autori: | , |
| Format: | Artigo |
| Jezik: | Latim |
| Izdano: |
Vilniaus Universitetas
2022
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| Teme: | |
| Online pristup: | https://www.redalyc.org/articulo.oa?id=692674321009 https://www.redalyc.org/journal/6926/692674321009/ https://www.redalyc.org/journal/6926/692674321009/html/ https://www.redalyc.org/journal/6926/692674321009/692674321009.epub https://www.redalyc.org/journal/6926/692674321009/movil https://doi.org/10.15388/LMR.2022.29755 |
| Oznake: |
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