1993The Quarterly Journal of EconomicsRequires access

Trading Volume and Serial Correlation in Stock Returns

J. Y. Campbell, Sanford Grossman, Jiangting Wang

Open publisher page 1,646 citations

Abstract

This paper investigates the relationship between aggregate stock market trading volume and the serial correlation of daily stock returns. For both stock indexes and individual large stocks, the first-order daily return autocorrelation tends to decline with volume. The paper explains this phenomenon using a model in which risk-averse “market makers” accommodate buying or selling pressure from “liquidity” or “noninformational” traders. Changing expected stock returns reward market makers for playing this role. The model implies that a stock price decline on a high-volume day is more likely than a stock price decline on a low-volume day to be associated with an increase in the expected stock return.

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What this paper is about

This paper investigates the relationship between aggregate stock market trading volume and the serial correlation of daily stock returns. For both stock indexes and individual large stocks, the first-order daily return autocorrelation tends to decline with volume. The paper explains this phenomenon using a model in which risk-averse “market makers” accommodate buying or selling pressure from “liquidity” or “noninformational” traders. Changing expected stock returns reward market makers for playing this role. The model implies that a stock price decline on a high-volume day is more likely than a stock price decline on a low-volume day to be associated with an increase in the expected stock return.

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Available abstract

This paper investigates the relationship between aggregate stock market trading volume and the serial correlation of daily stock returns. For both stock indexes and individual large stocks, the first-order daily return autocorrelation tends to decline with volume. The paper explains this phenomenon using a model in which risk-averse “market makers” accommodate buying or selling pressure from “liquidity” or “noninformational” traders. Changing expected stock returns reward market makers for playing this role. The model implies that a stock price decline on a high-volume day is more likely than a stock price decline on a low-volume day to be associated with an increase in the expected stock return.

Key concepts: Grossman, Stock (firearms), Volume (thermodynamics), Economics, Stock trading, Financial economics, Library science, History

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