Information Asymmetry Index: The View of Market Analysts

TL;DR

This paper introduces an innovative informational asymmetry index based on analyst perceptions using an Elo rating algorithm, validated through regression analysis with key firm proxies.

Contribution

It presents a novel index of informational asymmetry derived from analyst judgments, integrating an Elo rating system and validating it with empirical regression analysis.

Findings

The index correlates well with established proxies of informational asymmetry.

Four significant variables influencing the index: coverage, volatility, Tobin's q, and size.

The model provides a useful tool for future research on informational asymmetry.

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.