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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| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2025-06-01
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| Series: | FinTech |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2674-1032/4/2/22 |
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