Nonlinear high-frequency stock market time series: Modeling and combine forecast evaluations

DOI10.1080/03610918.2019.1597117zbMath1497.62313OpenAlexW2940267990WikidataQ128036181 ScholiaQ128036181MaRDI QIDQ5082682

Min Cherng Lee, Wen Cheong Chin

Publication date: 21 June 2022

Published in: Communications in Statistics - Simulation and Computation (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/03610918.2019.1597117

zbMATH Keywords

realized volatilityheterogeneous autoregressive modelcombine forecast methods

Mathematics Subject Classification ID

Applications of statistics to economics (62P20) Time series, auto-correlation, regression, etc. in statistics (GARCH) (62M10) Applications of statistics to actuarial sciences and financial mathematics (62P05) Economic time series analysis (91B84)

Uses Software

• fpp

Cites Work

• Measuring volatility with the realized range
• Persistence in forecasting performance and conditional combination strategies
• A multiple regime smooth transition heterogeneous autoregressive model for long memory and asymmetries
• Measuring and forecasting volatility in Chinese stock market using HAR-CJ-M model
• Jump-robust volatility estimation using nearest neighbor truncation
• Fractionally integrated generalized autoregressive conditional heteroskedasticity
• Realized stochastic volatility with general asymmetry and long memory
• The Volatility of Realized Volatility
• On Bayesian Modeling of Fat Tails and Skewness
• Modeling and Forecasting Realized Volatility

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