Theoretical and Empirical Asset Pricing

A special issue of Risks (ISSN 2227-9091).

Deadline for manuscript submissions: 31 July 2025 | Viewed by 958

Special Issue Editor


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Guest Editor
1. Macquarie Business School, Macquarie University, Sydney, NSW 2109, Australia
2. Institute of Financial Studies, Southwestern University of Finance and Economics, Chengdu 610074, China
Interests: asset pricing, portfolio selection, and nonlinear financial market modeling

Special Issue Information

Dear Colleagues,

We are pleased to announce a Special Issue titled “Theoretical and Empirical Asset Pricing”. This Special Issue aims to bring together groundbreaking research that explores both the theoretical frameworks and empirical analyses shaping the current landscape of asset pricing. In recent years, the complexity of financial markets and the availability of vast datasets have catalyzed significant advancements in asset pricing models. These developments have enabled researchers to test and refine existing theories, as well as to propose new models that better capture market dynamics. This Special Issue seeks to provide a comprehensive overview of these advancements by featuring contributions that address a wide range of topics within the field.

Topics of interest for this Special Issue include, but are not limited to, the development and application of novel theoretical models that explain asset returns, risk factors, and market anomalies. Additionally, this issue will highlight empirical studies that leverage cutting-edge econometric techniques and large-scale data analysis to validate or challenge prevailing theories.

Dr. Kai Li
Guest Editor

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Keywords

  • asset pricing theories
  • portfolio selection
  • risk factors
  • market anomalies
  • asset pricing puzzles
  • behavioral finance
  • market efficiency

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Published Papers (1 paper)

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Research

21 pages, 699 KiB  
Article
Stock Market Hype: An Empirical Investigation of the Impact of Overconfidence on Meme Stock Valuation
by Richard Mawulawoe Ahadzie, Peterson Owusu Junior, John Kingsley Woode and Dan Daugaard
Risks 2025, 13(7), 127; https://doi.org/10.3390/risks13070127 - 1 Jul 2025
Viewed by 434
Abstract
This study investigates the relationship between overconfidence and meme stock valuation, drawing on panel data from 28 meme stocks listed from 2019 to 2024. The analysis incorporates key financial indicators, including Tobin’s Q ratio, market capitalization, return on assets, leverage, and volatility. A [...] Read more.
This study investigates the relationship between overconfidence and meme stock valuation, drawing on panel data from 28 meme stocks listed from 2019 to 2024. The analysis incorporates key financial indicators, including Tobin’s Q ratio, market capitalization, return on assets, leverage, and volatility. A range of overconfidence proxies is employed, including changes in trading volume, turnover rate, changes in outstanding shares, and alternative measures of excessive trading. We observe a significant positive relationship between overconfidence (as measured by changes in trading volume) and firm valuation, suggesting that investor biases contribute to notable pricing distortions. Leverage has a significant negative relationship with firm valuation. In contrast, market capitalization has a significant positive relationship with firm valuation, implying that meme stock investors respond to both speculative sentiment and traditional firm fundamentals. Robustness checks using alternative proxies reveal that turnover rate and changes in the number of shares are negatively related to valuation. This shows the complex dynamics of meme stocks, where psychological factors intersect with firm-specific indicators. However, results from a dynamic panel model estimated using the Dynamic System Generalized Method of Moments (GMM) show that the turnover rate has a significantly positive relationship with firm valuation. These results offer valuable insights into the pricing behavior of meme stocks, revealing how investor sentiment impacts periodic valuation adjustments in speculative markets. Full article
(This article belongs to the Special Issue Theoretical and Empirical Asset Pricing)
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