Noise Traders Incarnate: Describing a Realistic Noise Trading Process

Joel Peress and Daniel Schmidt

No 12434, CEPR Discussion Papers from Centre for Economic Policy Research

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.

Date: 2017-11
New Economics Papers: this item is included in nep-mst
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)

Downloads: (external link)
https://cepr.org/publications/DP12434 (application/pdf)

Related works:
Journal Article: Noise traders incarnate: Describing a realistic noise trading process (2021)
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:cpr:ceprdp:12434

Ordering information: This working paper can be ordered from
https://cepr.org/publications/DP12434

Access Statistics for this paper

More papers in CEPR Discussion Papers from Centre for Economic Policy Research 33 Great Sutton Street, London EC1V 0DX, UK.
Bibliographic data for series maintained by CEPR ().