Revisiting Volume vs. GARCH Effects Using Univariate and Bivariate GARCH Models: Evidence from U.S. Stock Markets

This paper tests for the generalized autoregressive conditional heteroscedasticity (GARCH) effect on U.S. stock markets for different periods and reexamines the findings in Lamoureux and Lastrapes (Journal of Finance 45(1):221–229, 1990) by using alternative proxies for information flow, which are included in the conditional variance equation of a GARCH model. We also examine the spillover effects of volume and turnover on the conditional volatility using a bivariate GARCH approach. Our findings show that volume and turnover have effects on conditional volatility and that the introduction of volume/turnover as exogenous variable(s) in the conditional variance equation reduces the persistence of GARCH effects as measured by the sum of the GARCH parameters. Our results confirm the existence of the volume effect on volatility, consistent with the findings by Lamoureux and Lastrapes (Journal of Finance 45(1):221–229, 1990) and others, suggesting that the earlier findings were not a statistical fluke. Our findings also suggest that, unlike other anomalies, the volume effect on volatility is not likely to be eliminated after discovery. In addition, our study rejects the pure random walk hypothesis for stock returns. Our bivariate analysis also indicates that there are no volume or turnover spillover effects on conditional volatility among the companies, suggesting that the volatility of a company’s stock return may not necessarily be influenced by the volume and turnover of other companies.