Journal of Behavioral and Experimental Finance

We have the data-set extracted from open source.

The data includes all subjects' answers to the questionnaire using in this paper.

Programs for time preference elicitation

Source Code for 'oTree: The Bubble Game'

This repository contains the companion code for the article oTree: Implementing experiments with dynamically determined data quantity to be published in a Special Issue on "Software for Experimental Economics" in the Journal of Behavioral and Experimental Finance. The experiment "market" that is provided as oTree application serves as a illustrative example for a simple stylized market simulation. Many individuals (1 ... N-1) are selling fruit. In each round, these sellers choose a kind of fruit and a selling price, whereas individual N (the buyer) needs to choose from which of those offers to buy. The implemenation follows the principle suggested in the paper, relying on "custom data models" from oTree's underlying Django framework. This project also illustrates how the admin interface extensions of the package otreeutils can be integrated in an experiment. This adds the functionality to observe data updates from custom data models in oTree's "session data viewer". Additionally, data exports for CSV and Excel contain all data from custom data models and an option to export the data in JSON format is available.

The database is sorted by investor code (CODEINVESTOR) and each investor presents their response to the survey questions in the 25 days. The variables of the emotional framework (ACTIVATION, EXPERIENCED EMOTIONS, EXPECTED EMOTIONS, BADNEWS, SEX , and PLEASURE) follow. The variable GENDER allows to evaluate the responses for the gender of the agents involved. Finally, the variables YSNB, NSYB, YSYB, NSNB allow to highlight the combination of incidental emotions.

GIMS is a z-Tree-based software for conducting asset market experiments. See the documentation file included in the dataset for instructions on how to use it.

We test if Cohn et al.’s (2015) experimental results on countercyclical risk aversion exhibited by financial professionals generalize to a standard student sample. In our sample, we do not find an effect of stock market bust or boom on subjects’ investments. We do not find a systematic emotional reaction, nor do we find an effect of variation in the emotional state (especially fear) on investment. Our results add to the literature documenting behavioral differences between financial professionals and non-professionals and, taking a policy perspective, underline the need for careful external validity checks of single sample experiments.