Abstract
Abstract We identify long-lived pricing errors through a model in which inattentive investors arrive stochastically to trade. The model’s parameters are structurally estimated using daily NYSE market-maker inventories, retail order flows, and prices. The estimated model fits empirical variances, autocorrelations, and cross-autocorrelations among our three data series from daily to monthly frequencies. Pricing errors for the typical NYSE stock have a standard deviation of 3.2 percentage points and a half-life of 6.2 weeks. These pricing errors account for 9.4$\%$, 7.0$\%$, and 4.5$\%$ of the respective daily, monthly, and quarterly idiosyncratic return variances.
Highlights
This paper studies the day-to-day, week-to-week, and month-to-month role that investors’ limited attention plays in a stock price deviations from the efficient price
This paper studies the joint dynamics of stock price movements and the trading of individuals, institutions, and market makers
We present a dynamic model in which individuals and institutions trade a risky asset in order to hedge an exogenous endowment shock
Summary
This paper studies the day-to-day, week-to-week, and month-to-month role that investors’ limited attention plays in a stock price deviations from the efficient (random walk) price. The paper develops a theoretical model of investors with varying levels of attention, tests the model’s implications for price changes and investors’ trading with empirical New York Stock Exchange (NYSE) data, and quantifies the economic effects of limited attention on asset prices by estimating a reduced form version of the theoretical model. The economic magnitude of the empirical estimation provides the paper’s most significant results: 8% of a stock’s daily idiosyncratic return variance and 25% of a its monthly idiosyncratic variance are due to transitory price changes (noise) and the trading variables explain 32% of this noise. The consistency between the theoretical model and empirical data of the lead-lag and contemporaneous correlations among investors’ trading and price changes provides support for the model’s impact of inattention in stocks’ return-generating process. Market clearing in models with two investor types implies that after any initial shock trades of one type are exactly equal and opposite to those from the other type
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