Nonlinear price dynamics of S&P 100 stocks

Gunduz Caginalp and Mark DeSantis

Physica A: Statistical Mechanics and its Applications, 2020, vol. 547, issue C

Abstract: The methodology presented provides a quantitative way to characterize investor behavior and price dynamics within a particular asset class and time period. The methodology is applied to a data set consisting of over 250,000 data points of the S&P 100 stocks during 2004–2018. Using a two-way fixed-effects model, we uncover trader motivations including evidence of both under- and overreaction within a unified setting. A nonlinear relationship is found between return and trend suggesting a small, positive trend increases the return, while a larger one tends to decrease it. The shape parameters of the nonlinearity quantify trader motivation to buy into trends or wait for bargains. The methodology allows the testing of any behavioral finance bias or technical analysis concept.

Keywords: S&P stocks; Trend; Nonlinear dynamics; Volume; Underreaction; Overreaction (search for similar items in EconPapers)
JEL-codes: G02 G12 G17 (search for similar items in EconPapers)
Date: 2020
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Persistent link: https://EconPapers.repec.org/RePEc:eee:phsmap:v:547:y:2020:i:c:s0378437119311902

DOI: 10.1016/j.physa.2019.122067

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