Predicting the Long-term Stock Market Volatility: A GARCH-MIDAS Model with Variable Selection
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- Fang, Tong & Lee, Tae-Hwy & Su, Zhi, 2020. "Predicting the long-term stock market volatility: A GARCH-MIDAS model with variable selection," Journal of Empirical Finance, Elsevier, vol. 58(C), pages 36-49.
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More about this item
Keywords
Stock market volatility; GARCH-MIDAS model; Variable selection; Penalized maximum likelihood; Adaptive-Lasso;All these keywords.
JEL classification:
- C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
- C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation
- C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
- G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates
NEP fields
This paper has been announced in the following NEP Reports:- NEP-ECM-2020-06-08 (Econometrics)
- NEP-ETS-2020-06-08 (Econometric Time Series)
- NEP-FMK-2020-06-08 (Financial Markets)
- NEP-FOR-2020-06-08 (Forecasting)
- NEP-ORE-2020-06-08 (Operations Research)
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