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Autoregressive conditional heteroscedasticity: a comparison of ARCH and random coefficient models

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Publication:900134
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DOI10.1016/0165-1765(88)90086-9zbMath1328.62540OpenAlexW2118797768WikidataQ126339291 ScholiaQ126339291MaRDI QIDQ900134

Christian C. P. Wolff

Publication date: 1 January 2016

Published in: Economics Letters (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/0165-1765(88)90086-9


Mathematics Subject Classification ID

Time series, auto-correlation, regression, etc. in statistics (GARCH) (62M10) Economic time series analysis (91B84)


Related Items

Random autoregressive models: A structured overview, Exact initial conditions for maximum likelihood estimation of state space models with stochastic inputs, ARCH modeling in finance. A review of the theory and empirical evidence, On the relation between GARCH and stable processes



Cites Work

  • Autoregressive Conditional Heteroscedasticity with Estimates of the Variance of United Kingdom Inflation
  • Some Estimators for a Linear Model with Random Coefficients
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