Overvaluation of Assets with Recent Strong Growth in Fundamentals

Last registered on March 06, 2024


Trial Information

General Information

Overvaluation of Assets with Recent Strong Growth in Fundamentals
Initial registration date
February 23, 2024

Initial registration date is when the trial was registered.

It corresponds to when the registration was submitted to the Registry to be reviewed for publication.

First published
March 06, 2024, 3:14 PM EST

First published corresponds to when the trial was first made public on the Registry after being reviewed.


Primary Investigator

UC Santa Cruz

Other Primary Investigator(s)

PI Affiliation
UC Santa Cruz

Additional Trial Information

On going
Start date
End date
Secondary IDs
Prior work
This trial does not extend or rely on any prior RCTs.
Superstar assets sustainably grow their value far into the future. Given that superstars are attractive and rare, that people tend to practice base rate neglect, and that regular assets can appear to grow like superstars for several periods, investors may overdiagnose the probability of assets being superstars and may overpay for such assets in the market. To assess this possibility, a laboratory experiment is presented in which subjects observe a limited history of a risky asset, are informed about the relevant base rates and movement probabilities, and must guess the posterior probabilities that the asset is a superstar as well as its final payoff and place a bid to purchase the asset.
External Link(s)

Registration Citation

Lopez-Vargas, Kristian and Cliff Nelson. 2024. " Overvaluation of Assets with Recent Strong Growth in Fundamentals." AEA RCT Registry. March 06. https://doi.org/10.1257/rct.13056-1.0
Experimental Details


Subjects will be shown risky assets. The performance of the asset will be displayed. Subjects will be asked to guess the probability that the asset is a superstar as well as the final payoff. Additionally, subjects will make a bid for the assets.
Intervention Start Date
Intervention End Date

Primary Outcomes

Primary Outcomes (end points)
The subjective probabilities that assets are superstars as well as the valuation of assets.
Primary Outcomes (explanation)
Valuation can be measured by the difference between the subject's guess for the final outcome and their bid for that asset.

Secondary Outcomes

Secondary Outcomes (end points)
Secondary Outcomes (explanation)

Experimental Design

Experimental Design
This is a within-subject design carried out in the laboratory. Subjects are presented with assets. In some rounds, superstar assets are known to be possible and in other rounds, subjects are told that all assets are regular assets. Superstar assets increase each period with a probability of 99% whereas regular assets increase each period with a probability of 50%. The final payoff of the asset happens at period 10.
Subjects observe the first 3 (or 6) periods. They make a guess for the final payout and place a bid for the asset. In those rounds where superstars are possible, subjects guess the posterior probability that an asset is a superstar. The prior probability of an asset being a superstar in rounds where superstars are possible is 2%.
Experimental Design Details
Not available
Randomization Method
This is a within-subject design. Subjects experience both treatment (superstar assets are possible) and control (superstar assets are not possible). They will experience a block of 5 rounds of each type. Which block comes first is determined at the time of the session by a random number generator.
Randomization Unit
Subjects are invited to the study using ORSEE, which may randomly invite blocks of students who are registered for the system. Additionally, whether treatment or control rounds come first is randomized each experimental session.
Was the treatment clustered?

Experiment Characteristics

Sample size: planned number of clusters
Doesn't apply.
Sample size: planned number of observations
Multiple variables for each of the 120 subjects.
Sample size (or number of clusters) by treatment arms
120 subjects.
Minimum detectable effect size for main outcomes (accounting for sample design and clustering)

Institutional Review Boards (IRBs)

IRB Name
U California Santa Cruz IRB #1
IRB Approval Date
IRB Approval Number