Volatility forecasting with machine learning and intraday commonality
We apply machine learning models to forecast intraday realized volatility (RV), by exploiting commonality in intraday volatility via pooling stock data together, and by incorporating a proxy for the market volatility. Neural networks dominate linear regressions and tree-based models in terms of perf...
| Hlavní autoři: | , , , |
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| Médium: | Journal article |
| Jazyk: | English |
| Vydáno: |
Oxford University Press
2023
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