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Heteroskedasticity in Stock Return Data: Volume versus GARCH Effects
Author(s) -
LAMOUREUX CHRISTOPHER G.,
LASTRAPES WILLIAM D.
Publication year - 1990
Publication title -
the journal of finance
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 18.151
H-Index - 299
eISSN - 1540-6261
pISSN - 0022-1082
DOI - 10.1111/j.1540-6261.1990.tb05088.x
Subject(s) - autoregressive conditional heteroskedasticity , heteroscedasticity , econometrics , conditional variance , economics , proxy (statistics) , arch , explanatory power , autoregressive model , stock (firearms) , variance (accounting) , stock market , volatility (finance) , financial economics , mathematics , statistics , mechanical engineering , philosophy , civil engineering , accounting , epistemology , engineering , paleontology , horse , biology
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.