2011/08/31 by Bence Tóth, Bence Toth, Imon Palit +2 · 1 citation
Decision Sciences · Economics, Econometrics and Finance · Mathematics · Physics and Astronomy · #Autocorrelation #Complex Systems and Time Series Analysis #Econometrics #Economics #Equity (law) #Finance #Financial Markets and Investment Strategies #Financial economics #Geography #Herd behavior #Herding #Mathematics #Order (exchange) #Statistics #Stock (firearms) #Stock Market Forecasting Methods #cond-mat.stat-mech #physics.soc-ph #q-fin.ST #q-fin.TR
paper · pdf · doi:10.1016/j.jedc.2014.10.007
published as Journal of Economic Dynamics and Control 51, 218-239 (2015) · 42 pages, 15 figures
openalex publication_date 2014/11/05 · arxiv created 2014/11/30 · arxiv updated 2014/12/02 · openalex created_date 2025/10/10 · openalex updated_date 2026/08/05
Order flow in equity markets is remarkably persistent in the sense that order signs (to buy or sell) are positively autocorrelated out to time lags of tens of thousands of orders, corresponding to many days. Two possible explanations are herding, corresponding to positive correlation in the behavior of different investors, or order splitting, corresponding to positive autocorrelation in the behavior of single investors. We investigate this using order flow data from the London Stock Exchange for which we have membership identifiers. By formulating models for herding and order splitting, as well as models for brokerage choice, we are able to overcome the distortion introduced by brokerage. On timescales of less than a few hours the persistence of order flow is overwhelmingly due to splitting rather than herding. We also study the properties of brokerage order flow and show that it is remarkably consistent both cross-sectionally and longitudinally.