Heteroskedasticity in Stock Return Data: Volume versus GARCH Effects

Christopher G Lamoureux, WILLIAM D. LASTRAPES

Research output: Contribution to journalArticle

580 Citations (Scopus)

Abstract

This paper provides empirical support for the notion that Autoregressive Conditional Heteroskedasticity (ARCH) in daily stock return data reflects time dependence in the process generating information flow to the market. Daily trading volume, used as a proxy for information arrival time, is shown to have significant explanatory power regarding the variance of daily returns, which is an implication of the assumption that daily returns are subordinated to intraday equilibrium returns. Furthermore, ARCH effects tend to disappear when volume is included in the variance equation. 1990 The American Finance Association

Original languageEnglish (US)
Pages (from-to)221-229
Number of pages9
JournalThe Journal of Finance
Volume45
Issue number1
DOIs
StatePublished - 1990
Externally publishedYes

Fingerprint

Generalized autoregressive conditional heteroscedasticity
Stock returns
Heteroskedasticity
Autoregressive conditional heteroskedasticity
Information flow
Time dependence
Trading volume
Finance

ASJC Scopus subject areas

  • Accounting
  • Finance
  • Economics and Econometrics

Cite this

Heteroskedasticity in Stock Return Data : Volume versus GARCH Effects. / Lamoureux, Christopher G; LASTRAPES, WILLIAM D.

In: The Journal of Finance, Vol. 45, No. 1, 1990, p. 221-229.

Research output: Contribution to journalArticle

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