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Semiparametric ARCH Models

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Author Info

  • Engle, Robert F
  • Gonzalez-Rivera, Gloria

Abstract

A semiparametric ARCH model is introduced with conditional first and second moments given by ARMA and ARCH formulations, and a conditional density that is approximated by a nonparametric density estimator. For several densities, the relative efficiency of the quasi-maximum likelihood estimator is compared with maximum likelihood under correct specification. These potential efficiency gains for a fully adaptive procedure are compared in a Monte Carlo experiment with the observed gains from using the semiparametric procedure, and it is found that the estimator captures a substantial proportion of the potential. The estimator is applied to daily stock returns and to the British pound/dollar exchange rate.

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Bibliographic Info

Article provided by American Statistical Association in its journal Journal of Business and Economic Statistics.

Volume (Year): 9 (1991)
Issue (Month): 4 (October)
Pages: 345-59

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Handle: RePEc:bes:jnlbes:v:9:y:1991:i:4:p:345-59

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