Do artificial neural networks provide improved volatility forecasts: Evidence from Asian markets
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DOI: 10.1007/s12197-023-09629-8
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Cited by:
- Li, Zhao-Chen & Xie, Chi & Wang, Gang-Jin & Zhu, You & Zeng, Zhi-Jian & Gong, Jue, 2024. "Forecasting global stock market volatilities: A shrinkage heterogeneous autoregressive (HAR) model with a large cross-market predictor set," International Review of Economics & Finance, Elsevier, vol. 93(PB), pages 673-711.
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More about this item
Keywords
Volatility; Forecasting; Neural Networks; Machine Learning; VaR; ES;All these keywords.
JEL classification:
- C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
- C58 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Financial Econometrics
- C63 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Computational Techniques
- G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates
- G17 - Financial Economics - - General Financial Markets - - - Financial Forecasting and Simulation
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