The Hybrid Forecast of S&P 500 Volatility ensembled from VIX, GARCH and LSTM models

被引：0
|
作者：
Roszyk, Natalia [1 ]
S´lepaczuk, Robert [2 ]
机构：
[1] University of Warsaw, Faculty of Economic Sciences, Quantitative Finance Research Group, Ul. Dluga 44/50, Warsaw,00-241, Poland
[2] University of Warsaw, Faculty of Economic Sciences, Department of Quantitative Finance and Machine Learning, Quantitative Finance Research Group, Ul. Dluga 44/50, Warsaw,00-241, Poland
来源：
arXiv |
关键词：
Deep learning - Financial time series - Financial time series analyse - Forecasting models - Hybrid forecasting - Hybrid forecasting model - Hyper-parameter - Hyperparameter tuning - LSTM-GARCH - Machine-learning - S&P 500 index - Time-series analysis - VIX index - Volatility forecasting - Walk forward - Walk-forward process;
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摘要：
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