Nonlinear Price Dynamics of S&P 100 Stocks

Physica A: Statistical Mechanics and its Applications, Forthcoming

47 Pages Posted: 10 Jul 2019

See all articles by Gunduz Caginalp

Gunduz Caginalp

University of Pittsburgh - Department of Mathematics

Mark DeSantis

Chapman University - The George L. Argyros School of Business & Economics

Date Written: July 9, 2019

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

JEL Classification: G02, G12, G17

Suggested Citation

Caginalp, Gunduz and DeSantis, Mark, Nonlinear Price Dynamics of S&P 100 Stocks (July 9, 2019). Physica A: Statistical Mechanics and its Applications, Forthcoming , Available at SSRN: https://ssrn.com/abstract=3417410

Gunduz Caginalp

University of Pittsburgh - Department of Mathematics ( email )

507 Thackeray Hall
Pittsburgh, PA 15260
United States
412-624-8339 (Phone)
412-624-8397 (Fax)

Mark DeSantis (Contact Author)

Chapman University - The George L. Argyros School of Business & Economics ( email )

333 N. Glassell
Orange, CA 92866
United States

Do you have a job opening that you would like to promote on SSRN?

Paper statistics

Downloads
86
Abstract Views
535
rank
398,300
PlumX Metrics