Title: Performance in stock transactions by gender: an application with quantile regression models

Authors: Robson Braga; Luis Paulo Lopes Fávero; Talles Vianna Brugni; Joanilia Neide De Sales Cia

Addresses: Department of Technology and Social Sciences, State University of Bahia, Avenida Jonas David Fadini, 300, Estela Reis, CEP 45.823-035 – Eunápolis, BA, Brazil ' School of Economics, Business Administration and Accounting, University of Sao Paulo, Av. Prof. Luciano Gualberto, 908 – FEA1, Cidade Universitária, CEP 05.508-010 – São Paulo, SP, Brazil ' School of Economics, Business Administration and Accounting, University of Sao Paulo, Av. Prof. Luciano Gualberto, 908 – FEA3, Cidade Universitária, CEP 05.508-010 – São Paulo, SP, Brazil ' School of Economics, Business Administration and Accounting, University of Sao Paulo, Av. Prof. Luciano Gualberto, 908 – FEA3, Cidade Universitária, CEP 05.508-010 – São Paulo, SP, Brazil

Abstract: Our study tries to identify if there are performance differences between men and women in stock investment decisions. We use experimental methodology and count on the participation of 1,050 volunteers who took decisions in virtual environment, similar to a real online home broker for stock trading. Through quantile regression models, we have found evidence that women get results lower than men when decisions involve gains when decisions involve losses, women lose as much as men. These results demonstrate behavioural biases associated with disposition and endowment effects, as well as aspects related to loss aversion. As a result, we present a contribution on the field of behavioural finance, especially on the literature of gender diversity, which presents a controversial debate in several studies.

Keywords: investment behaviour; investment decisions; gender diversity; quantile regression; stock trading platform.

DOI: 10.1504/IJSSS.2018.089472

International Journal of Society Systems Science, 2018 Vol.10 No.1, pp.74 - 89

Received: 10 Nov 2016
Accepted: 27 May 2017
Published online: 26 Jan 2018 *

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