WHY DOES THE STANDARD GARCH(1, 1) MODEL WORK WELL?

DOI10.1142/S0129183107011261zbMath1200.91257arXivphysics/0503027MaRDI QIDQ3500189

P. Norouzzadeh, Gholam Reza Jafari, Alireza Bahraminasab

Publication date: 3 June 2008

Published in: International Journal of Modern Physics C (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/physics/0503027

zbMATH Keywords

Markov processtime series analysisGARCH processes

Mathematics Subject Classification ID

Economic time series analysis (91B84)

Related Items (1)

Equity premium prediction: taking into account the role of long, even asymmetric, swings in stock market behavior

Cites Work

• Generalized autoregressive conditional heteroscedasticity
• Modelling critical and catastrophic phenomena in geoscience. A statistical physics approach. Papers based on the lectures at the workshop on `models of earthquakes: physical approaches', Kolkata, India, December 2005.
• Temporal Aggregation of Garch Processes
• Autoregressive Conditional Heteroscedasticity with Estimates of the Variance of United Kingdom Inflation

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