Up: 1:2

Pricing stocks with yardsticks and sentiments

Sebastían Martínez Bustos; Jørgen Vitting Andersen; Michel Miniconi; Andrzej Nowak; Magdalena Roszczynska-Kurasinska; David Brée

Algorithmic Finance (2011), 1:2, 183-190
DOI: 10.3233/AF-2011-013

Published: Abstract, PDF.
Archived: SSRN.


Human decision making by professionals trading daily in the stock market can be a daunting task. It includes decisions on whether to keep on investing or to exit from a market subject to huge price swings, and also how to price in news or rumors attributed to a specific stock. The question then arises how professional traders, who specialize in daily buying and selling large amounts of a given stock, know how to properly price a given stock on a given day. Here we introduce the idea that people use heuristics, or “rules of thumb”, in terms of “yard sticks” from the performance of the other stocks in a stock index. The under or over performance with respect to such a yard stick then signifies a general negative or positive sentiment of the market participants towards a given stock. Using empirical data of the Dow Jones Industrial Average, stocks are shown to have daily performances with a clear tendency to cluster around the measures introduced by the yard sticks. We illustrate how sentiments, most likely due to insider information, can influence the performance of a given stock over period of months, and in one case years.

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Philip Maymin

University of Bridgeport

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Jayaram Muthuswamy

Kent State University

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Kenneth J. Arrow

Stanford University

Herman Chernoff

Harvard University

David S. Johnson

AT&T Labs Research

Leonid Levin

Boston University

Myron Scholes

Stanford University

Michael Sipser

Massachusetts Institute of Technology

Richard Thaler

University of Chicago

Stephen Wolfram

Wolfram Research

Editorial Board

Associate Editors

Peter Bossaerts

California Institute of Technology

Emanuel Derman

Columbia University

Ming-Yang Kao

Northwestern University

Pete Kyle

University of Maryland

David Leinweber

Lawrence Berkeley National Laboratory

Richard J. Lipton

Georgia Tech

Avi Silberschatz

Yale University

Robert Webb

University of Virginia

Affiliate Editors

Giovanni Barone-Adesi

University of Lugano

Bruce Lehmann

University of California, San Diego

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Online ISSN: 2157-6203
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