Honors Theses
Date of Award
Spring 5-8-2026
Document Type
Undergraduate Thesis
Department
Economics
First Advisor
John Conlon
Second Advisor
Ken Johnson
Third Advisor
Ryan Rholes
Relational Format
Honors Capstone
Abstract
This thesis studies how individuals judge asset price paths and bubbles from graphical data. It primarily investigates whether individuals can differentiate simulated asset price paths that are generated from pure random walks, and graphs that have a bubble element. This question is important because inventors and ordinary people often interpret price paths visually.
To test this, the project creates simulated asset price paths using random walks and bubble multipliers. The survey has four types of graphs: pure random walks, random walks with a 25% bubble, random walks with a 50% bubble, and random walks with a 75% bubble. The graphs are mixed together and shown to survey participants who are asked if each graph appears to have a bubble or not. The participants’ responses are then used to calculate correct positive rates and false positive rates. Bayes’ Rule is applied to the probabilities of each participant’s responses to analyze how they should update their beliefs that bubbles are possible. The results show that weaker bubble elements provide weaker evidence for Bayesian updates, whereas larger bubble elements provide stronger evidence. Also, the results show that pure random walks can be misidentified as containing a bubble.
Overall, this thesis argues that graphical evidence of asset price paths should be interpreted carefully. If a chart looks bubbly, it can provide useful information to the investor, but it does not automatically prove that bubbles exist.
Recommended Citation
Vining, Cooper P., "Perception of Asset Price Bubbles in Graphical Data" (2026). Honors Theses. 3489.
https://egrove.olemiss.edu/hon_thesis/3489