Heteroskedasticity in Stock Return Data: Volume versus GARCH Effects
用实证数据支持了股票日收益率中的自回归条件异方差（ARCH）反映了信息流到达市场的时间依赖性，发现日成交量作为信息到达的代理变量，对日收益率方差有显著解释力，且加入成交量后ARCH效应趋于消失。
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.