STOCK PRICE PREDICTION AND SIMULATION USING GEOMETRIC BROWNIAN MOTION-KALMAN FILTER: A COMPARISON BETWEEN KALMAN FILTER ALGORITHMS
Stocks have high-profit potential but also have high risk. Many people have ways to forecast stock prices. The Geometric Brownian Motion (GBM) method forecasts stock prices. The data used in this study are closing stock price data from July 1, 2021 to August 31, 2021 taken from Yahoo! Finance. The s...
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| Główni autorzy: | , , , , , |
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| Format: | Artigo |
| Język: | Inglês |
| Wydane: |
Universitas Pattimura
2025-01-01
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| Seria: | Barekeng |
| Hasła przedmiotowe: | |
| Dostęp online: | https://ojs3.unpatti.ac.id/index.php/barekeng/article/view/12740 |
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