Bootstrap forecast intervals for asymmetric volatilities via EGARCH model

DOI10.1080/03610926.2015.1014105zbMath1462.62543OpenAlexW2317557839MaRDI QIDQ2979589

Dong Wan Shin, Hyeyoung Maeng

Publication date: 25 April 2017

Published in: Communications in Statistics - Theory and Methods (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/03610926.2015.1014105

zbMATH Keywords

bootstrappingvolatility forecastingasymmetric volatilityEGARCH model

Mathematics Subject Classification ID

Time series, auto-correlation, regression, etc. in statistics (GARCH) (62M10)

Cites Work

• Correction to “Automatic Block-Length Selection for the Dependent Bootstrap” by D. Politis and H. White
• An econometric analysis of asymmetric volatility: theory and application to patents
• Quasi-maximum-likelihood estimation in conditionally heteroscedastic time series: a stochastic recurrence equations approach
• Bootstrap prediction for returns and volatilities in GARCH models
• The jackknife and the bootstrap for general stationary observations
• Bootstrapping forecast intervals in ARCH models
• Computationally efficient bootstrap prediction intervals for returns and volatilities in ARCH and GARCH processes
• Conditional Heteroskedasticity in Asset Returns: A New Approach
• Automatic Block-Length Selection for the Dependent Bootstrap

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