Equity order flow is persistent in the sense that buy orders tend to be followed by buy orders and sellorders tend to be followed by sell orders. For equity order flow this persistence is extremely long-ranged, with positive correlations spanning thousands of orders, over time intervals of up to several days. Such persistence in supply and demand is economically important because it influences the market impact as a function of both time and size and because it indicates that the market is in a sense out of equilibrium. Persistence can be caused by two types of behavior : (1) Order splitting, in which a single investor repeatedly places an order of the same sign, or (2) herding, in which different investors place orders of the same sign. We develop a method to decompose the autocorrelation function into splitting and herding components and apply this to order flow data from the London Stock Exchange containing exchange membership identifiers. Members typically act as brokers for other investors, so that it is not clear whether patterns we observe in brokerage data also reflect patterns in the behavior of single investors. To address this problem we develop models for the distortion caused by brokerageand demonstrate that persistence in order flow is overwhelmingly due to order splitting by single investors. At longer time scales we observe that different investors' behavior is anti-correlated. We show that this is due to differences in the response to price-changing vs. non-price-changing market orders .
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 .
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Equity order flow is
Order flow in equity markets is remarkably
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buy orders tend to be followed by buy orders and sellorders tend to be followed by sell orders. For equity order flow this persistence is extremely long-ranged, with positive correlations spanning
order signs (to buy or sell) are positively autocorrelated out to time lags of tens of
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over time intervals of up to several days. Such persistence in supply and demand is economically important because it influences the market impact as a function of both time and size and because it indicates that the market is in a sense out of equilibrium. Persistence can be caused by two types of behavior : (1) Order splitting, in which a single investor repeatedly places an order of the same sign, or (2) herding, in which different investors place orders of the same sign. We develop a method to decompose the autocorrelation function into splitting and herding components and apply this to
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
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containing exchange
for which we have
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Members typically act as brokers for other investors, so that it is not clear whether patterns we observe in brokerage data also reflect patterns in the behavior of single investors. To address this problem we develop models for the distortion caused by brokerageand demonstrate that persistence in
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
R
order splitting by single investors. At longer time scales we observe that different investors' behavior is anti-correlated. We show that this is due to differences in the response to price-changing vs. non-price-changing market orders
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