2000/08/07 by Parameswaran Gopikrishnan, Vasiliki Plerou, Xavier Gabaix +1 · 10 citations
Economics, Econometrics and Finance · Physics and Astronomy · #Chaos control and synchronization #Complex Systems and Time Series Analysis #Econometrics #Economics #Financial Risk and Volatility Modeling #Financial economics #Geography #Monetary economics #Stock (firearms) #Volatility (finance) #cond-mat.dis-nn #cond-mat.stat-mech #q-fin.ST
paper · pdf · doi:10.1103/physreve.62.r4493
published as Phys. Rev. E. (Rapid Comm.), 62 (2000) R4493. · 4 pages, two-column format, four figures
arxiv created 2000/08/07 · openalex publication_date 2000/10/01 · arxiv updated 2009/11/30 · openalex created_date 2016/06/24 · openalex updated_date 2026/08/05
We quantitatively investigate the ideas behind the often-expressed adage ``it takes volume to move stock prices,'' and study the statistical properties of the number of shares traded Q_\ensuremathΔt for a given stock in a fixed time interval \ensuremathΔt. We analyze transaction data for the largest 1000 stocks for the two-year period 1994--95, using a database that records every transaction for all securities in three major US stock markets. We find that the distribution P(Q_\ensuremathΔt) displays a power-law decay, and that the time correlations in Q_\ensuremathΔt display long-range persistence. Further, we investigate the relation between Q_\ensuremathΔt and the number of transactions N_\ensuremathΔt in a time interval \ensuremathΔt, and find that the long-range correlations in Q_\ensuremathΔt are largely due to those of N_\ensuremathΔt. Our results are consistent with the interpretation that the large equal-time correlation previously found between Q_\ensuremathΔt and the absolute value of price change |G_\ensuremathΔt| (related to volatility) are largely due to N_\ensuremathΔt.