Abstract
Wavelet methods and artificial neural networks are incorporated to examine the forecasting performance of the daily closing price of the Microsoft stock, NASDAQ:MSFT. An experimental analysis is performed to demonstrate improved performance of the wavelet neural network. Results in this study suggest that for these neurowavelet models a long history with a short training is ideal for stock prediction. This model could be used by investors, financial managers, or others to enhance their ability to select desired stocks.
| Original language | English |
|---|---|
| Pages (from-to) | 12-25 |
| Number of pages | 14 |
| Journal | Proceedings of the Asian Technology Conference in Mathematics |
| State | Published - 2021 |
| Externally published | Yes |
| Event | 26th Asian Technology Conference in Mathematics, ATCM 2021 - Virtual, Online Duration: Dec 13 2021 → Dec 15 2021 |