Date of Award
Spring 6-12-2026
Document Type
Dissertation
Degree Name
Ph.D. in Business
Organizational Unit
Daniels College of Business
First Advisor
Jack Strauss
Second Advisor
Ryan Elmore
Third Advisor
Erik Mekelburg
Fourth Advisor
Mohammad Mahoor
Copyright Statement / License for Reuse
All Rights Reserved.
Keywords
Black Scholes, Herding, Kalshi, Polymarket, Prediction markets
Abstract
This dissertation examines prediction markets as emerging financial and informational venues, evaluating in two complementary studies whether their prices aggregate dispersed beliefs efficiently and whether they conform to established benchmarks of financial economics. Across more than two thousand binary contracts traded on Kalshi and Polymarket, the dissertation tests both the behavioral process through which crowd beliefs form and the financial structure through which those beliefs are priced.
The first paper, Herding in Prediction Markets, investigates whether traders converge in ways consistent with herd behavior. Building on the cross-sectional standard deviation (CSSD) and cross-sectional absolute deviation (CSAD) frameworks of Christie & Huang (1995) and Chang et al. (2000), the paper estimates aggregate, asymmetric, and category-specific dispersion models on daily prediction-market returns. Aggregate CSSD tests reveal little market-wide herding, but CSAD regressions uncover significant concavity between dispersion and market returns, indicating selective belief convergence as price movements intensify. Herding is most pronounced in Sports, Elections, Financials, and Companies, where outcomes are binary and information environments are shared, while Entertainment, Economics, and Crypto retain greater heterogeneity of expectations.
The second paper, The Price Is Right? Prediction Markets, Black–Scholes, and the Wisdom of the Crowds, benchmarks prediction-market prices against derivative implied probabilities across cryptocurrencies, equity indexes, gold, eggs, and Federal Reserve rate decisions. Cointegration, Mincer–Zarnowitz, and threshold error-correction models show that prediction-market prices maintain long-run equilibrium with their no-arbitrage benchmarks but systematically under-react to benchmark signals, with efficiency varying by asset class and converging toward full alignment as settlement approaches.
Taken together, the two papers demonstrate that prediction markets function simultaneously as behavioral aggregation mechanisms and as financial pricing venues. Belief convergence is selective and domain-dependent, while price formation is broadly anchored to financial theory yet sluggish in adjusting to it. The dissertation contributes to behavioral finance, market microstructure, and the empirical evaluation of prediction markets as policy-relevant forecasting instruments.
JEL— C45, C51, C58, G14, G17
Copyright Date
6-2026
Publication Statement
Copyright is held by the author. User is responsible for all copyright compliance.
Rights Holder
Mark Schneider
Provenance
Received from ProQuest
File Format
application/pdf
Language
English (eng)
Extent
202 pgs
File Size
16.6 MB
Recommended Citation
Schneider, Mark, "Prediction Markets as Financial Markets: Herding or Wisdom of the Crowds" (2026). Electronic Theses and Dissertations. 2756.
https://digitalcommons.du.edu/etd/2756