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GARCHNet: Value-at-Risk Forecasting with GARCH Models Based on Neural Networks
This paper proposes a new GARCH specification that adapts the architecture of a long-term short memory neural network (LSTM). It is shown that classical GARCH models generally give good results in financial modeling, where high volatility can be observed. In particular, their high value is often pra...
| Autores principales: | , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
Springer US
2023
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| Materias: | |
| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10201522/ https://www.ncbi.nlm.nih.gov/pubmed/37362594 http://dx.doi.org/10.1007/s10614-023-10390-7 |