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There's more to volatility than volume
Authors:László Gillemot  J Doyne Farmer
Institution:1. Santa Fe Institute , 1399 Hyde Park Road, Santa Fe , NM 87501 , USA;2. Budapest University of Technology and Economics , H-1111 Budapest , Budafoki út 8 , Hungary;3. Budapest University of Technology and Economics , H-1111 Budapest , Budafoki út 8 , Hungary
Abstract: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 analyse recent results of Ane and Geman (2000 Ane, T and Geman, H. 2000. Order flow, transaction clock, and normality of asset returns. J. Finance, 55(5): 22592284. Crossref], Web of Science ®] Google Scholar]: J. Finance, 55, 2259–2284) and Gabaix et al. (2003 Gabaix, X, Gopikrishnan, P, Plerou, V and Stanley, H.E. 2003. A theory of power-law distributions in financial market fluctuations. Nature, 423: 267270. Crossref], PubMed], Web of Science ®] Google Scholar]: Nature, 423, 267–270), 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.
Keywords:Financial markets  Volatility  Volume  Subordinated processes
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