  It is widely believed that fluctuations in transaction volume, as reflected
in the number of transactions and to a lesser extent their size, are the main
cause of clustered volatility. Under this view bursts of rapid or slow price
diffusion reflect bursts of frequent or less frequent trading, which cause both
clustered volatility and heavy tails in price returns. We investigate this
hypothesis using tick by tick data from the New York and London Stock Exchanges
and show that only a small fraction of volatility fluctuations are explained in
this manner. Clustered volatility is still very strong even if price changes
are recorded on intervals in which the total transaction volume or number of
transactions is held constant. In addition the distribution of price returns
conditioned on volume or transaction frequency being held constant is similar
to that in real time, making it clear that neither of these are the principal
cause of heavy tails in price returns. We analyze recent results of Ane and
Geman (2000) and Gabaix et al. (2003), and discuss the reasons why their
conclusions differ from ours. Based on a cross-sectional analysis we show that
the long-memory of volatility is dominated by factors other than transaction
frequency or total trading volume.
