Anticipatory Gains and Event-Driven Losses in Blockchain-Based Fan Tokens: Evidence from the FIFA World Cup

ArXiv ID: 2403.15810 “View on arXiv”

Authors: Unknown

Abstract

National football teams increasingly issue tradeable blockchain-based fan tokens to strategically enhance fan engagement. This study investigates the impact of 2022 World Cup matches on the dynamic performance of each team’s fan token. The event study uncovers fan token returns surged six months before the World Cup, driven by positive anticipation effects. However, intraday analysis reveals a reversal of fan token returns consistently declining and trading volumes rising as matches unfold. To explain findings, we uncover asymmetries whereby defeats in high-stake matches caused a plunge in fan token returns, compared to low-stake matches, intensifying in magnitude for knockout matches. Contrarily, victories enhance trading volumes, reflecting increased market activity without a corresponding positive effect on returns. We align findings with the classic market adage “buy the rumor, sell the news,” unveiling cognitive biases and nuances in investor sentiment, cautioning the dichotomy of pre-event optimism and subsequent performance declines.

Keywords: fan tokens, event study, blockchain, market sentiment, cryptocurrency

Complexity vs Empirical Score

  • Math Complexity: 4.0/10
  • Empirical Rigor: 7.5/10
  • Quadrant: Street Traders
  • Why: The paper relies primarily on event studies and intraday regression analysis using real-world cryptocurrency and football data, with sophisticated implementation details, but the mathematical foundations are standard econometric techniques without advanced theoretical derivations.
  flowchart TD
    A["Research Goal:<br>Impact of FIFA World Cup matches<br>on Fan Token Performance"] --> B["Data Collection &amp; Methodology"]
    B --> C["Event Study: Pre-World Cup<br>Analysis (6-month window)"]
    B --> D["Intraday Analysis: During<br>Matches (Returns &amp; Volume)"]
    C --> E["Key Findings"]
    D --> E
    subgraph E ["Outcomes"]
        direction LR
        F["Anticipatory Gains:<br>Returns surged pre-event"]
        G["Event-Driven Losses:<br>Returns declined during matches"]
        H["Asymmetry:<br>High-stake/Knockout losses<br>severely impacted returns"]
        I["Volume-Volatility:<br>Victories boosted volume<br>but not returns"]
    end
    style F fill:#d4edda,stroke:#155724
    style G fill:#f8d7da,stroke:#721c24
    style H fill:#fff3cd,stroke:#856404
    style I fill:#cce5ff,stroke:#004085