Heteroskedasticity in Stock Return Data: Volume versus GARCH Effects.

This paper provides empirical support for the notion that autoregressive conditional heteroskedasticity 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, autoregressive conditional heteroskedasticity effects tend to disappear when volume is included in the variance equation. Copyright 1990 by American Finance Association.