Salience Effects in Portfolio Selection
Last registered on January 17, 2020

Pre-Trial

Trial Information
General Information
Title
Salience Effects in Portfolio Selection
RCT ID
AEARCTR-0005311
Initial registration date
January 17, 2020
Last updated
January 17, 2020 10:45 AM EST
Location(s)
Region
Primary Investigator
Affiliation
Heinrich-Heine University Düsseldorf
Other Primary Investigator(s)
PI Affiliation
Frankfurt School of Finance and Management
Additional Trial Information
Status
In development
Start date
2020-01-20
End date
2020-02-29
Secondary IDs
Abstract
A large experimental literature on choices between two reduced (or simple) lotteries has documented two robust facts: First, if both lotteries are symmetric, then subjects are typically risk averse; that is, with symmetric risks a large majority of subjects chooses the option with less variance in outcomes. Second, if at least one of the lotteries is skewed, subjects often reveal a preference for positive skewness, which can even result in risk-seeking behavior; that is, a large majority of subjects chooses a sufficiently positively skewed risk even if it is the option with more variance in outcomes.

In this study, we ask how robust the observed patterns in these simple choices are to increasing the complexity of the problem along two dimensions: we increase the number of available options and/or replace the reduced lotteries by portfolios (i.e., convex combinations of reduced lotteries), where the latter means that the final outcomes are not stated, but have to be inferred. The experiment is designed to test the predictions of salience theory of choice under risk (Bordalo et al., 2012) for such portfolio selection problems against those of naive decision rules like the 1/N-heuristic (e.g., Benartzi and Thaler, 2001), which predict that subjects diversify naively by investing equal shares into the available reduced lotteries.
External Link(s)
Registration Citation
Citation
Dertwinkel-Kalt, Markus and Mats Köster. 2020. "Salience Effects in Portfolio Selection." AEA RCT Registry. January 17. https://doi.org/10.1257/rct.5311-1.0.
Sponsors & Partners
Sponsor(s)
Experimental Details
Interventions
Intervention(s)
Section 4 of the Pre-Analysis Plan describes the experimental design in detail.
Intervention Start Date
2020-01-20
Intervention End Date
2020-02-29
Primary Outcomes
Primary Outcomes (end points)
Indicators of the choice between two or many portfolios (i.e., convex combinations of lotteries) or two reduced lotteries.
Primary Outcomes (explanation)
Section 4 of the Pre-Analysis Plan contains a detailed description of the primary outcomes.
Secondary Outcomes
Secondary Outcomes (end points)
The number of memorized outcomes of the available reduced lotteries.
Secondary Outcomes (explanation)
Section 4 of the Pre-Analysis Plan contains a detailed description of the secondary outcomes.
Experimental Design
Experimental Design
We study the choice between two or many portfolios (i.e., convex combinations of two reduced lotteries). We implement two treatments: one with skewed lotteries (including 12 choices between two portfolios, 12 choices between many portfolios, and 12 choices between two reduced lotteries) and one with symmetric lotteries (including 12 choices between two portfolios, 12 choices between many portfolios, and 6 choices between two reduced lotteries). A detailed description of the experimental design is provided in Section 4 of the Pre-Analysis Plan.
Experimental Design Details
Not available
Randomization Method
Randomization done by a computer.
Randomization Unit
Individual
Was the treatment clustered?
Yes
Experiment Characteristics
Sample size: planned number of clusters
300 individuals
Sample size: planned number of observations
9900 choices
Sample size (or number of clusters) by treatment arms
150 individuals in the treatment with skewed lotteries and 150 individuals in the treatment with symmetric lotteries
Minimum detectable effect size for main outcomes (accounting for sample design and clustering)
IRB
INSTITUTIONAL REVIEW BOARDS (IRBs)
IRB Name
IRB Approval Date
IRB Approval Number
Analysis Plan
Analysis Plan Documents
Pre-Analysis Plan

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SHA1: f088f5f7ab7183d46b2a6be026e147c26f6c344b

Uploaded At: January 17, 2020