Nonlinear modelling and forecasting of S\& P 500 volatility

DOI10.1016/S0378-4754(01)00411-6zbMath1008.91099OpenAlexW2029450437MaRDI QIDQ1614020

Berndt Pilgram, Peter Verhoeven, Michael McAleer, Alistair I. Mees

Publication date: 3 September 2002

Published in: Mathematics and Computers in Simulation (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/s0378-4754(01)00411-6

zbMATH Keywords

parametric modelvolatility forecastingnon-parametric modelnonlinear Markov modelling

Mathematics Subject Classification ID

Economic time series analysis (91B84) Statistical methods; economic indices and measures (91B82)

Related Items (3)

Nonlinear modelling and forecasting of S\& P 500 volatility ⋮ Confidence bands in nonparametric time series regression ⋮ Detecting volatility persistence in GARCH models in the presence of the leverage effect

Cites Work

• ARCH modeling in finance. A review of the theory and empirical evidence
• Nonlinear modelling and forecasting of S\& P 500 volatility
• Generalized autoregressive conditional heteroscedasticity
• On selecting models for nonlinear time series
• Embedding as a modeling problem
• Autoregressive Conditional Heteroscedasticity with Estimates of the Variance of United Kingdom Inflation
• NECESSARY AND SUFFICIENT MOMENT CONDITIONS FOR THE GARCH(r,s) AND ASYMMETRIC POWER GARCH(r,s) MODELS
• Unnamed Item

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