Paper: arXiv 2409.06272

Authors: Roberto Frota Decourt, Heitor Almeida, Philippe Protin, Matheus R. C. Gonzalez

Abstract

The purpose of the research was to build an index of informational asymmetry with market and firm proxies that reflect the analysts’ perception of the level of informational asymmetry of companies. The proposed method consists of the construction of an algorithm based on the Elo rating and captures the perception of the analyst that choose, between two firms, the one they consider to have better information. After we have the informational asymmetry index, we run a regression model with our rating as dependent variable and proxies used by the literature as the independent variable to have a model that can be used for other researches that need to measure the level of informational asymmetry of a company. Our model presented a good fit between our index and the proxies used to measure informational asymmetry and we find four significant variables: coverage, volatility, Tobin q, and size.

Complexity vs Empirical Score

  • Math Complexity: 3.5/10
  • Empirical Rigor: 6.0/10
  • Quadrant: Street Traders — practical and empirical, lighter on theory

Why this score: The paper presents an innovative application of the Elo rating algorithm to quantify information asymmetry using analyst pairwise surveys and validates it against standard financial proxies via empirical regression models. While mathematically straightforward, the methodology offers solid empirical relevance, though details on survey sample size and exact code implementation are somewhat lacking.

Research Flowchart

  flowchart TD
    A[Goal: Measure Informational Asymmetry via Analyst Perception] --> B[Input: Pairwise Analyst Comparisons of Firms]
    B --> C[Compute Elo Rating Algorithm]
    C --> D[Generate Informational Asymmetry Index]
    D --> E[Regression Model: Index vs. Literature Proxies]
    E --> F[Outcome: Good Model Fit & 4 Key Drivers]

    subgraph Key_Drivers [Significant Variables]
        F --- G[Coverage, Volatility, Tobin's Q, Size]
    end

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0 of 35 cited works are in the corpus; resolved via arXiv source bundles, Semantic Scholar and OpenAlex. Corpus-wide: 2518 linked papers.