Discussion Paper Details

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Title: Noise Traders Incarnate: Describing a Realistic Noise Trading Process

Author(s): JoŽl Peress and Daniel Schmidt

Publication Date: November 2017


Programme Area(s): Financial Economics

Abstract: We estimate a realistic process for noise trading to help theorists calibrate noisy rational expectations models. For this purpose, we characterize the trades initiated by individual investors, who are natural candidates for the role of noise traders because their trades are, on average, cross-correlated and loss making. We use transactions data from a retail brokerage house, small TAQ trades, and flows to retail mutual funds, obtaining consistent results. We find that noise trading can be treated as approximately i.i.d. at monthly and lower frequencies but that weekly and daily trades are serially correlated; the distribution of noise trading is less heavy-tailed at lower frequency but conforms to a normal only for quarterly data. We provide a complete description of these processes, including estimates of their standard deviation. In line with theory, the estimates are higher for more liquid and volatile stocks; they also suggest that the prevalence of noise trading has declined over time.

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Bibliographic Reference

Peress, J and Schmidt, D. 2017. 'Noise Traders Incarnate: Describing a Realistic Noise Trading Process'. London, Centre for Economic Policy Research.