| Title |
Akcijų kainų ARIMA ir LSTM prognozavimo metodų lyginamoji analizė / |
| Translation of Title |
Comparative analysis of stock price ARIMA and LSTM forecasting methods. |
| Authors |
Bielskis, Aivaras ; Belovas, Igoris |
| DOI |
10.15388/LMR.2022.29755 |
| Full Text |
|
| Is Part of |
Lietuvos matematikos rinkinys. Ser. B.. Vilnius : Vilniaus universiteto leidykla. 2022, t. 63, p. 21-27.. ISSN 0132-2818. eISSN 2335-898X |
| Keywords [eng] |
time series ; neural networks ; forecasting ; ARIMA ; SARIMA ; LSTM |
| Abstract [eng] |
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 (Amazon, Apple, Google, Netflix, and Tesla companies) simulations are evaluated using MAE and MRE measures. The conclusions obtained in the work made it possible to identify shortcomings of the approaches and specify guidelines for improvements and further research. |
| Published |
Vilnius : Vilniaus universiteto leidykla |
| Type |
Journal article |
| Language |
Lithuanian |
| Publication date |
2022 |
| CC license |
|
