Hybrid GARCH-LSTM Forecasting for Foreign Exchange Risk
This study proposes a hybrid forecasting model that integrates the Generalized Autoregressive Conditional Heteroskedasticity (GARCH) model with a Long Short-Term Memory (LSTM) neural network to estimate Value at Risk (VaR) in the Rwandan foreign exchange market. The model is designed to capture both...
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| Principais autores: | , , |
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| Formato: | Artigo |
| Idioma: | Inglês |
| Publicado: |
MDPI AG
2025-06-01
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| Series: | FinTech |
| Assuntos: | |
| Acceso en liña: | https://www.mdpi.com/2674-1032/4/2/22 |
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