Cargando…
Artificial Neural Network Based Non-linear Transformation of High-Frequency Returns for Volatility Forecasting
This paper uses Long Short Term Memory Recurrent Neural Networks to extract information from the intraday high-frequency returns to forecast daily volatility. Applied to the IBM stock, we find significant improvements in the forecasting performance of models that use this extracted information compa...
| Autor principal: | |
|---|---|
| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
Frontiers Media S.A.
2022
|
| Materias: | |
| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8873984/ https://www.ncbi.nlm.nih.gov/pubmed/35224478 http://dx.doi.org/10.3389/frai.2021.787534 |