  We examine the relationship between trading volumes, number of transactions,
and volatility using daily stock data of the Tokyo Stock Exchange. Following
the mixture of distributions hypothesis, we use trading volumes and the number
of transactions as proxy for the rate of information arrivals affecting stock
volatility. The impact of trading volumes or number of transactions on
volatility is measured using the generalized autoregressive conditional
heteroscedasticity (GARCH) model. We find that the GARCH effects, that is,
persistence of volatility, is not always removed by adding trading volumes or
number of transactions, indicating that trading volumes and number of
transactions do not adequately represent the rate of information arrivals.
