Experimental Design
We address our research question (i.e., if participants extrapolate from recent signed returns, and how attributes of recent returns affect portfolio choice) with a simple, standard investment experiment. Subjects participate in an investment experiment consisting of 27 independent decisions. In each decision task, participants allocate an endowment of 10,000 experimental currency units between a risky and a risk-free asset. To inform their investment decisions, past returns are shown. While past return distributions differ in the number of negative vs. positive returns, they have stationary means, standard deviations, and skewness, and thus provide the same information about the expected value and variability of future returns. We interact the main treatment (mostly positive vs. mostly negative returns) with three different visualization treatments: tables, bar plots, and colored (pos vs. negative) bar plots. The different visualizations potentially create different levels of treatment salience. For every third investment decision, we also elicit participants' beliefs about the next period return. In addition, we also implement several between-subject treatment variations: 1) standard experiment described above, 2) alteration with different ordering of visualization formats, 3) alteration controlling for 'streaks', i.e., successively positive (negative) recent returns, and 4) alteration controlling for 'recency bias', i.e., more recent vs. more distant prevalence of positive (negative) returns. Thus, in total, we will have 2 sources of within-subject variation (sign distribution of observed returns, visualization format), and 4 sources of between-subject variation (standard, visualization ordering, streaks vs. no streaks, recent vs. distant sign prevalence).
The experiment concludes with a short survey eliciting investment experience and basic sociodemographic information (age, gender, education, self-assessed risk aversion). At the end of the experiment, one of the 27 investment decisions is randomly chosen and implemented for payment. The investment outcome is then divided by 1000 and rounded to the nearest Euro amount. In case the chosen round contained belief elicitation, probability estimates are incentivized via a ranked probability score. We expect an average payoff between 10 and 13 EUR per participant.
The experiment is implemented in Qualtrics. We are going to run the experiment at WU Labs and we expect that participants will complete it in approximately 30 to 45 minutes. Note, we abstain from any form of deception.