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Les modéles ARCH en finance : un point sur la théorie et les résultats empiriques

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  • Tim BOLLERSLEV
  • Ray Y. CHOU
  • Narayanan JAYARAMAN
  • Kenneth F. KRONER

Abstract

Although volatility clustering has a long history as a salient empirical regularity characterizing high frequency speculative prices, it was not until recently that applied researchers in finance have recognized the importance of explicitly modeling time varying second order moments. Instrumental in most of these empirical studies has been the Autoregressive Conditionnal Heteroskedasticity (ARCH) model introduced by Engle (1982). This paper contains an overview of some of the developments in the formulations of ARCH models and a survey of numerous empirical applications using financial data. Several suggestions for future research, including the implementation and tests of competing asset pricing theories, market microstructure models, information transmission mechanisms, dynamic hedging strategies and the pricing of derivative assets, are also discussed.

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Bibliographic Info

Article provided by ENSAE in its journal Annals of Economics and Statistics.

Volume (Year): (1991)
Issue (Month): 24 ()
Pages: 1-59

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Handle: RePEc:adr:anecst:y:1991:i:24:p:01

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Cited by:
  1. Abdelhamid El Bouhadi, 2003. "Conditional Volatility Of Most Active Shares Of Casablanca Stock Exchange," Finance 0305007, EconWPA, revised 10 Oct 2003.
  2. El Bouhadi, Abdelhamid & Achibane, Khalid, 2009. "The Predictive Power of Conditional Models: What Lessons to Draw with Financial Crisis in the Case of Pre-Emerging Capital Markets?," MPRA Paper 19482, University Library of Munich, Germany.

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