ARCH modeling in finance. A review of the theory and empirical evidence
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 Conditional Heteroskedasticity (ARCH) model introduced by Engle (1982). This paper contains an overview of some of the developments in the formulation of ARCH models and a survey of the 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. © 1992.
Duke Scholars
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- Econometrics
- 4905 Statistics
- 3802 Econometrics
- 3801 Applied economics
- 1403 Econometrics
- 1402 Applied Economics
- 0104 Statistics
Citation
Published In
DOI
ISSN
Publication Date
Volume
Issue
Start / End Page
Related Subject Headings
- Econometrics
- 4905 Statistics
- 3802 Econometrics
- 3801 Applied economics
- 1403 Econometrics
- 1402 Applied Economics
- 0104 Statistics