Heteroscedasticity in stock returns data revisited: volume versus GARCH effects
M. F. Omran, E. McKenzie
Abstract
M. F. Omran, E. McKenzie
Abstract
The results of Lamoureux and Lastrapes (Journal of Finance, 45, 221-29, 1990) are extended to the UK stock market, and the study examines, in particular, their finding that GARCH modelling captures the serial dependence in volume of trade. Using data on 50 UK companies, we find that although the parameter estimates of the GARCH model become insignificant when volume of trade is used in the conditional variance of returns, the autocorrelations of the squared residuals still exhibit a highly significant GARCH effects. Evidence is found that there is a strong association in the timing of innovational outliers in returns and volume. The results suggest that a threshold model for volume and returns could prove a useful route to pursue in future research.
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The results of Lamoureux and Lastrapes (Journal of Finance, 45, 221-29, 1990) are extended to the UK stock market, and the study examines, in particular, their finding that GARCH modelling captures the serial dependence in volume of trade. Using data on 50 UK companies, we find that although the parameter estimates of the GARCH model become insignificant when volume of trade is used in the conditional variance of returns, the autocorrelations of the squared residuals still exhibit a highly significant GARCH effects. Evidence is found that there is a strong association in the timing of innovational outliers in returns and volume. The results suggest that a threshold model for volume and returns could prove a useful route to pursue in future research.
Key concepts: Heteroscedasticity, Autoregressive conditional heteroskedasticity, Econometrics, Economics, Stock (firearms), Outlier, Volume (thermodynamics), Conditional variance