Forecasting volatility under fractality, regime-switching, long memory and Student-\(t\) innovations

DOI10.1016/j.csda.2010.03.005zbMath1284.91590OpenAlexW2057936711MaRDI QIDQ2445719

Thomas C. H. Lux, Leonardo Morales-Arias

Publication date: 14 April 2014

Published in: Computational Statistics and Data Analysis (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.csda.2010.03.005

zbMATH Keywords

long memoryinternational volatility forecastingmultiplicative volatility modelsStudent-\(t\) innovations

Mathematics Subject Classification ID

Time series, auto-correlation, regression, etc. in statistics (GARCH) (62M10) Applications of statistics to actuarial sciences and financial mathematics (62P05) Statistical methods; risk measures (91G70) Economic time series analysis (91B84) Stochastic models in economics (91B70)

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Cites Work

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• Generalized Levinson--Durbin and Burg algorithms.
• Correcting the Errors: Volatility Forecast Evaluation Using High-Frequency Data and Realized Volatilities
• Modeling and Forecasting Realized Volatility
• Forecasting multifractal volatility

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