Order imbalance and individual stock returns: theory and evidence

By Tarun Chordia, Avanidhar Subrahmanyam. 2004

533 citations recorded by the source corpus.

Subfields: Accounting, Economics and Econometrics, Finance

View Paper: https://www.semanticscholar.org/paper/2f2e2349dd7579d043279fb75638c23f2d7d1127

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Citations in the corpus

Trading activity, realized volatility and jumps (2010, unknown): “17 Indeed, Chordia and Subrahmanyam (2004) state that “Intuition suggests that the implications of a reported volume of one million shares generated by 500,000 shares of seller initiated trades and 500,000 shares of buyer-initiated trades are very different from those generated by one million shares”
Trading imbalances, predictable reversals, and cross-stock price pressure (2008, background): “Our approach addresses concerns that a large number of buy (sell) orders during a given week increases the probability that prices end the week at the ask (bid) price (see Blume and Stambaugh, 1983; Chordia and Subrahmanyam, 2004; Subrahmanyam, 2005b).”
Relation between bid–ask spread, impact and volatility in order-driven markets (2006, background): “…finally obtain for the average cost of a single market order: CMðT 1Þ ¼ hvSi 2hvi 1 hvR1ðvÞi hvi , ð18Þ yThese long ranged correlations were also noted in e.g. Chordia and Subrahmanyam (2004) and Hopman (2002), but the detailed shape of the tail of C(‘) was not investigated, and its long-memory…”
Correlated Trading and Returns (2008, unknown): “Chordia and Subrahmanyam (2004) note that, in the short-term, liquidity imbalances could also be positively correlated with future returns when the imbalances are autocorrelated.”
Identifying Expensive Trades by Monitoring the Limit Order Book (2017, background): “Some authors (e.g. Chordia et al. (2002), Chordia and Subrahmanyam (2004) and Lee et al. (2004)) show that order flow imbalance can be used to predict returns.”
Does Option Trading Convey Stock Price Information (2014, background): “The empirical evidence that supports this prediction exists both at the market level (Chordia, Roll, and Subrahmanyam, 2002) and in the cross section of stocks (Chordia and Subrahmanyam, 2004).”
Liquidity and Market Efficiency: A Large Sample Study (2010, background): “Recent empirical studies in the market microstructure literature also show increasing interest in the relationship between order flows and stock returns (e.g. Chordia et al., 2002, 2005; Chordia and Subrahmanyam, 2004; Subrahmanyam, 2008).”
Individual Investor Trading and Stock Returns (2008, unknown): “Chordia and Subrahmanyam (2004) look at the profitability of trading strategies that use previous day trading imbalances signed with the Lee and Ready (1991) algorithm.”
High‐Frequency Trading around Large Institutional Orders (2019, unknown): “We also set up a “placebo” sample 9It is inspired by the “imbalance” measure of Chordia and Subrahmanyam (2004). The precise definition of directionality is: |S-B|/(S+B), where B and S are buy and sell share volume, respectively.”
Order Flow and Expected Option Returns (2015, unknown): “This idea is implied by Chordia and Subrahmanyam (2004) in their model.”